PUAD 701 Ohio State University Government Information Sources Annotated Bibliography

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Business Finance

PUAD 701

Ohio State University

PUAD

Description

Learning Outcomes

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Upon completion of this module, you should be able to do the following:

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  • Research and evaluate scholarly and professional resources.
  • Explain the relevance of scholarly and professional resources for understanding and developing recommendations for addressing your proposal topic or problem.
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Reading & Preparation

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  • Review the Capstone Project Overview.
  • Start working on your Annotated Bibliography, which is due at the end of this week.

Two annotated bibliographies for your capstone. Make sure that your annotations clearly summarize both articles and explain their relevance to the problem stated in the proposal.

NB attached are Recommended Reading and Resources

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PUAD 701 1 Government Organization Information Sources Information on government organizations is typically the most difficult to find because there is not a database that presents the necessary information in a consolidated fashion. Typically, you will have to scour a particular agency’s website to find information you need. Many agencies produce annual reports that are a good source for finding summary information students will need, particularly, understandable presentations of financial information. USA.gov is probably the best site for finding up-to-date links and information on the national, state, local and tribal governments in the United States. Also, budget or finance offices within a large agency or external administrative agencies, such as a city budget or finance office, typically provide useful information - audit reports or comprehensive annual financial reports (CAFRs) are often good sources for summary agency personnel and budget figures such as revenues and expenditures. For example, the Ohio Legislation Service Commission provides useful summaries of the purpose, function, staffing, and budget of each state agency in Ohio. Also, the Ohio Auditor of State provides a searchable database of financial audit reports and CAFRs for almost all state and local agencies in Ohio. State and Local Governments The National Conference of State Legislatures provides links to states’ legislative web sites including legislation, government reports, state law or statutes, and state Constitutions. For example, if you want information on governments in Ohio, look to: U.S. Government Agencies At the national level, the following websites have useful information: Catalogue of Federal Domestic Assistance: Provides a full listing of all Federal programs available to State and local governments (including the District of Columbia); federally-recognized Indian tribal governments; Territories (and possessions) of the United States; domestic public, quasi- public, and private profit and nonprofit organizations and institutions; specialized groups; and individuals. It contains detailed program descriptions for 2,165 Federal assistance programs. General Accountability Office: A source for thousands of reports summarizing and analyzing the financial and programmatic performance of national government agencies and important public policy issues on behalf of Congress. Office of Management of Budget: The best centralized source for summaries of agencies activities and current and historical budget information and analysis. International Government Organizations Department of State: Provides detailed, summaries on all the countries in the world. United Nations: Provides extensive information on international issues and on the countries of the world from an international perspective. PUAD 701 1 Nonprofit Information Sources Form 990 Nonprofits must regularly file information with the national government about their finances, organizational leadership, etc. This is done on the Internal Revenue Service (IRS) Form 990. The Form 990 is particularly helpful for finding budget information. For example, Part VIII of the form offers a sufficiently detailed presentation of organizational program revenue sources and Part IX shows a useful breakdown of expenses by major categories or functions. Also, Part VII and Schedule J, Part II, which is usually filed with Form 990, lists the names and salaries of key officers and board members of an organization. Not-for-Profit Websites Much of the information you will need to find about nonprofits can be found on a nonprofit website that compiles information about and compares organizations in the not-for-profit sector: GuideStar: One of the best sites for detailed information on non-profit organizations, including helpful web links and links to Form 990 filings. You must register with the site to access most of the information; however, registration is free. Charity Navigator: Excellent source of summary information on nonprofit organizations’ finances, mission, and top leadership and provides links to recent news stories about the organization. The site also offers numeric ratings of each nonprofit based on multiple measures of financial performance and on transparency and accountability. The ratings offer one method for thinking about how to evaluate the efficiency and effectiveness of nonprofit, including comparative assessment. You must register with the site to access most of the information; however, registration is free, particularly by reviewing the most recent Form 990 which should be available on the website. However, you will have to register (for free) on the site to access much of the necessary information. Foundation Center: This is an excellent site for finding financial information about non-profits, particularly foundations and other organizations that provide grant funding to other organizations. The site also has summary information about nonprofits and one of the most comprehensive databases for finding the Form 990 filings that most nonprofits must send to the IRS. The Form 990 contains detailed financial, organizational, and other information on a nonprofit. Internal Revenue Service: The IRS provides information on the tax code and legal requirements for nonprofit organizations. The site also enables searches to find out the legal classification of nonprofit charities. Any information not available on a site like GuideStar typically can be found on the particular nonprofit organization’s own website.       A  Short  Guide  for  Conducting  Research  Interviews     An  interview  is  a  great  way  to  get  information  and  insight  into  a  research  topic,  and  it  can  be   fun  for  you  and  the  person  you  are  interviewing.  Most  people  enjoy  sharing  their  expertise,   experiences,  and  insights  if  they’ve  been  given  enough  time  to  do  so.  If  you  plan  to  interview  a   child,  a  patient,  or  another  vulnerable  individual  OR  will  ask  for  medical,  psychological,  or  legal   information,  ask  your  professor  about  the  ethical  standards  that  apply  to  your  discipline,   including  those  relating  to  confidentiality  and  obtaining  written  consent  to  use  the  material   gathered.    The  following  is  a  step-­‐by-­‐step  guide  to  conducting  a  productive  interview.         Before  the  Interview     • Ask  the  person  you  would  like  to  interview  for  an  appointment  as  quickly  as  you  can.    This   gives  you  the  best  chance  of  getting  a  “yes”  in  answer  to  your  request  because  the  window   of  opportunity  for  meeting  with  the  person  is  the  longest  possible.  Be  courteous  and  as   flexible  as  you  can  in  arranging  the  date  and  time  of  the  interview.  It  is  a  good  idea  to   confirm  the  date,  time,  and  place  of  the  interview  in  an  email.           • When  you  ask  for  the  interview,  be  clear  about  the  purpose  of  the  interview,  how  the   information  will  be  used,  and  how  long  the  interview  will  take  (30  minutes  or  an  hour  are   typical  timeframes).  Be  clear  about  whether  the  information  given  will  be  attributed  to  the   person  being  interviewed  or  will  be  anonymous.         • For  a  face-­‐to-­‐face  interview,  be  sure  to  arrange  a  meeting  place  where  you  and  the  person   being  interviewed  feel  safe  and  comfortable.  If  you  are  interviewing  a  professional,  his  or   her  office  during  regular  business  hours  might  be  a  good  arrangement,  but  other  public   places  may  also  be  appropriate.     • Try  to  arrange  for  a  face-­‐to-­‐face  interview,  but  phone  or  email  interviews  can  also  work.     Providing  written  questions  to  get  written  answers  is  not  ideal  because  it  is  hard  to  ask  for   clarification  or  to  ask  follow-­‐up  questions  about  answers  that  surprise  you,  but  email   interviews  can  be  effective  if  you  give  yourself  enough  time  to  follow  up  with  additional   questions  or  requests  for  clarification.         • Research  your  topic  and,  if  possible,  the  person  you  plan  to  interview  before  the  interview   occurs.  Then  you  can  focus  your  questions  and  your  limited  interview  time  on  getting   insights  and  information  not  available  through  other  types  of  research.         writingcenter.appstate.edu                  828-­‐262-­‐3144              writingctr@appstate.edu     Updated  03/2014   •     •             • Prepare  your  questions  in  advance:         o Be  sure  your  questions  are  clear.         o Unless  you  want  a  very  clear  or  precise  answer,  questions  that  can’t  be  answered   “yes”  or  “no”  may  be  the  best  for  encouraging  fuller  answers,  and  may  give  you  an   important  explanation  or  interesting  story.       o Try  to  create  questions  that  don’t  include  assumptions  or  bias.  For  example,  “What   do  you  think  about  this  issue?”  is  better  than  “Don’t  you  think  that  (inserting  your   own  view  on  the  issue)?”       The  particular  questions  you  ask  will  be,  of  course,  related  to  the  subject  of  your  research   and  should  be  tailored  carefully  to  get  you  the  information  you  need.  For  an  interview  of  an   expert,  some  typical  questions  might  include:     o Why  did  you  get  into  this  field?     o What  education,  training,  or  other  preparation  did  you  need  to  get  into  the  field?   o What  are  you  working  on  now  and  what  is  interesting  about  it?     o What  do  you  spend  the  most  time  doing?     o What  continues  to  inspire  you  or  hold  your  interest  in  this  field?   o Where  is  this  field  going  in  the  future?    What  will  you  be  working  on?   o Is  there  anything  else  you  think  I  should  know?   Consider  whether  you  want  to  record  the  interview.  Generally,  this  is  a  good  practice   because  it  will  give  you  an  exact  record  of  the  interview,  frees  you  up  to  think  about  the   responses  to  your  questions  rather  than  taking  careful  notes  (though  you  still  might  want  to   make  some  notes),  and  the  person  you  interview  will  be  reassured  that  you  will  quote   accurately.  However,  in  a  few  situations,  such  as  an  interview  on  a  sensitive  subject  or  if  you   are  interviewing  a  very  shy  person,  recording  may  make  the  person  interviewed  uneasy  and   they  may  be  more  guarded.  Generally,  however,  it  makes  good  sense  to  record  research   interviews.  Plan  to  take  a  your  own  recording  device.     During  the  Interview     • Arrive  on  time  and  be  friendly  and  courteous  in  greeting  the  person  you  are  interviewing.  It   may  be  helpful  to  remind  them  of  the  purpose  of  the  interview.     writingcenter.appstate.edu                  828-­‐262-­‐3144              writingctr@appstate.edu     Updated  03/2014   •   •   •   Make  a  note  of  (or  record)  the  full  name  of  the  person  you  are  interview,  along  with  the   date,  time,  and  place  of  the  interview,  so  that  you  can  create  proper  citations  for  the   interview  in  your  paper.       If  you  are  recording  the  interview,  you  must  ask  the  person  you  are  interviewing  for   permission  to  record  the  conversation,  preferably  with  their  agreement  recorded  on  your   recording  device  at  the  first  part  of  the  interview.  (In  some  states,  the  law  requires  you  to   get  the  consent  of  anyone  you  record.)  If  they  decline,  go  ahead  and  conduct  the  interview   without  recording  it,  keeping  as  careful  notes  as  you  can.       Relax  and  have  fun  at  your  interview.   o Having  prepared  your  questions  in  advance  and  researched  the  background  of  your   topic,  you  will  be  free  to  listen  to  the  responses  to  your  questions  with  greater   understanding  and  ask  important  follow-­‐up  questions.     o Respect  the  time  of  the  person  you  are  interviewing,  keeping  to  the  agreed  upon   timeframe  or  asking  if  he  or  she  can  continue  a  little  longer.     o Thank  the  person  for  the  interview.     After  the  Interview     • Immediately  after  the  interview,  consider  transcribing  the  recording  you’ve  made  because  it   will  help  you  to  understand  any  nuances  that  you  might  have  missed  during  the  interview.     If  you  don’t  transcribe  your  recording  or  didn’t  record  the  interview,  go  over  your  notes  to   make  sure  they  are  complete.     • Send  a  thank-­‐you  note  or  email  even  if  you  thanked  the  person  you  interviewed  in  person.         • Properly  cite  the  information  gained  in  the  interview  in  your  research  paper  according  to   your  documentation  style.         • Consider  sending  the  finished  research  paper  to  the  person  you  interviewed  with  a  final   note  of  thanks.  As  an  expert,  he  or  she  will  probably  be  interested  and  may  become  a   valuable  academic  or  professional  contact.   writingcenter.appstate.edu                  828-­‐262-­‐3144              writingctr@appstate.edu     Updated  03/2014   Journal of Public Administration Research and Theory Advance Access published March 23, 2012 Desperately Seeking Management: Understanding Management Quality and Its Impact on Government Performance Outcomes under the Clean Air Act Alexander C. Heckman Franklin University This study analyzes the impact of management quality, spending, problem severity, and political factors on states’ air pollution control outcomes and provides insights for improving the measures and methods used in public management and government performance research. The analysis illustrates the importance of selecting proper outcome measures and taking into account the interaction of management and spending when conducting empirical analysis into the causes of government performance. Additionally, the author demonstrates the benefits of conducting comparative empirical analysis using different, but theoretically connected, outcome measures. The findings and analysis presented should be of particular interest to public administration scholars seeking to conduct research that produces practical insights for public managers and policy makers on improving public management and government performance. THE CHALLENGE OF MEASURING MANAGEMENT Public management studies consistently find that measures of management quality and the use of certain management practices are positively related to government performance. However, the results of these studies often do not provide useful, generalizable, guidance about what practitioners should do to improve management practice. Unfortunately, management quality measures are frequently based on the subjective opinions of employees within the organizations studied or they have been too narrowly defined for a particular organizational or programmatic context to be of general applicability (Brudney, O’Toole, and Rainey 2000; Donahue 2004; Meier and O’Toole 2002; Nicholson-Crotty and O’Toole This article would not have been possible without the support and guidance of Trevor Brown at the Glenn School at The Ohio State University. I also thank Anand Desai and the anonymous reviewers for their suggestions for improving this study and Jenine Larrabee and Kyle Yaggi for their assistance in improving the quality of the manuscript. Thanks also to R. Steven Brown and Mary Blakeslee of the Environmental Council of the States; Rachel Weiss of the National Institute on Money in State Politics; Jim DeMocker and Tom McMullen of the USEPA; Neal Johnson (now with Pearson Education) and the good people at the Pew Charitable Trust; and the helpful state and local public servants in 47 states, for helping me to obtain and understand the data for this analysis. Address correspondence to the author at alexander.heckman@franklin.edu. doi:10.1093/jopart/mur068 ª The Author 2012. Published by Oxford University Press on behalf of the Journal of Public Administration Research and Theory, Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 ABSTRACT 2 Journal of Public Administration Research and Theory STUDY OVERVIEW This study uses the GPP management measure to test management’s impact on environmental outcomes—a wholly different context than past studies using the GPP. The specific questions addressed in the study are: 1) Does state management quality impact air pollution control outcomes? 2) What is the impact of management quality on air pollution control outcomes relative to other state-level factors related to problem severity, resources, and the political environment? The study incorporates design elements and data that make it well-suited for answering these questions. The important study elements include:  Model Specification: The model specification was developed using the Mazmanian-Sabatier implementation model (MSIM) illustrated in Figure 1, which is a well-established policy implementation model.  Outcome Measures: The analysis uses two different measures of performance outcomes including a unique outcome measure that estimates reductions in air pollution emissions due to national Clean Air Act (CAA). This second measure better reflects the outcomes sought by Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 2004; O’Toole, Meier, and Nicholson-Crotty 2005; Selden and Sowa 2004). Additionally, management measures used in the literature are often opaque as to what constitutes good management. For instance, Meier and O’Toole (2002) used the residual from a regression model of a superintendent’s salary as a measure of managerial quality and found that good management had a positive impact on student learning outcomes. Although findings from such studies may support the notion that good management produces good performance, they shed little light on general steps for improving public management practice and policy implementation outcomes. The lack of concrete, yet general, measures of management quality represents a major obstacle to producing pragmatic insights about the public management-government performance relationship (Boyne 2003, 2004; Boyne et al. 2005). Although Meier and O’Toole (2002) have stated that this measurement challenge is ‘‘intractable,’’ developing more useful, general measures of management quality is essential if public administration research is to produce practical knowledge for improving public management practice that results in better government performance. A significant exception to the lack of general and concrete measures of management quality is the management grades assigned to the 50 states in 1999, 2001, 2005, and 2008 by the Government Performance Project (GPP), which is currently managed by the Pew Center on the States. The GPP management capacity measure provides detailed, general, criteria that clearly define good management practice. The GPP grades represent the best, criteria-based, multidimensional measure that is regularly applied to a large number of governments in the United States (Borins 2005; Ingraham, Joyce, and Kneedler 2003). Studies using the GPP suggest that it is a promising way to operationalize the concept of management quality in a general way that provides practical insights into what constitutes good management practice (Burke and Wright 2002; Coggburn and Schneider 2003; Donahue, Selden, and Ingraham 2000; Knack 2002). Heckman Management Quality and Its Impact on Government Performance 3 Figure 1 Mazmanian and Sabatier Implementation Success Model  Causal Measures and Data: The analysis also uses measures of management quality and interest group influence that more accurately capture these concepts than similar studies (e.g., Lester, Franke, and Bowman 1983). Also, the study includes better data on the total amounts spent within each state on air pollution control efforts. The data were collected by the author and provide the most accurate estimates available of these expenditures.  Comparative, Large-N Analysis: Two different measures of air pollution control outcomes affected by the same causal variables are modeled, which enables a comparative analysis of the empirical results. Also, air pollution outcomes for 47 states are modeled, providing generalizable results not found in many studies examining government performance, particularly studies on policy implementation. Together, these elements create a unique study that sheds new light on the management-performance connection and the causal factors affecting national air pollution control outcomes. CONTEXT FOR ASSESSING MANAGEMENT IMPACT National air pollution policy provides a useful context for assessing the impact of state management quality on performance outcomes because it provides a common policy design in regards to air pollution control, but state-level implementation efforts and characteristics are critical determinants of the extent to which policy goals are achieved (Woods, Konisky, and Bowman 2009). The CAA is the primary air pollution control legislation in the United States. Under the CAA, the US Environmental Protection Agency (USEPA) sets national ambient air quality standards to ensure basic protection of human health and natural resources, but state and local governments are primarily responsible for enforcement of the Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 policy makers and achieved by policy implementers, than similar studies using only aggregate emission outcome measures (e.g., Carson, Jeon, and McCubbin 1997; Lowry 1992). 4 Journal of Public Administration Research and Theory THEORETICAL MODEL AND MANAGEMENT QUALITY MEASURE The MSIM is one of the most comprehensive and empirically tested policy implementation theories and was developed to model intergovernmental implementation situations like the one examined in this study—see Figure 1 (McFarlane and Gruebel 2006; Zheng 2000). The MSIM states that government performance is the result of three categories of factors (Mazmanian and Sabatier 1989): Statutory: The statutory structure of a policy is set in law by elected officials to direct and constrain policy implementation. According to the MSIM, policy implementation should be more successful when goals are clearly understood, there is a sound understanding of the causes of the problem, and sufficient resources are provided to achieve policy goals. Under the CAA, the policy design and goals are set by the national government and is the same for all states. Total spending on implementing air pollution control policies is the main statutory variation across the states. The combined decisions of national, state, and certain local governments determine the level of resources spent on air pollution control efforts within each state. Nonstatutory: Nonstatutory factors are not in direct control of national policy makers but impact the policy outcomes achieved by officials implementing the policy. Relevant nonstatutory factors include the support or opposition of the general public and influential interest groups for the policy and the skill of implementing officials or management quality within each state. 1 Appendix 1 summarizes the changes made to the CAA in 1990 that are most relevant to this analysis. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 policy. All 50 states have been delegated responsibility for implementing the CAA provisions and states face financial and other sanctions from the USEPA if they fail to adequately carry out their duties (ECOS 2007; USEPA 2007). States and certain local environmental agencies implement the CAA by monitoring air quality, inspecting facilities and enforcing air pollution regulations. Amendments to the CAA enacted in 1990 further increased the regulatory role states play and strengthened the ability of the states to meet national air pollution standards (Rabe 2006).1 Evidence of the prominent role states play in carrying the CAA can be seen in USEPA statistics. Nearly all the air pollution data in the USEPA’s databases are collected and reported by the states (Brown and Green 2001; ECOS and USEPA 1999). States also bear most of the financial responsibility for enforcing air pollution control programs. On average, more than $1 billion per year is spent on air pollution control activities within each of the 47 states included in this study. However, according to the National Association of Clean Air Agencies (NACAA 2009), less than 25% of all the revenue for state and local air pollution control activities comes from the national government. Complying with CAA requirements and avoiding federal sanctions is an important goal of each state government, including the state environmental agency, the legislature, and top executive officials. Researchers generally agree that states have been active at carrying out their duties under the CAA, although the level of commitment and competency varies by state (Rabe 2007). Therefore, differences in states’ spending, management quality, and political environments should determine the air pollution control outcomes they achieve (Lester 1995; Rabe 2006). This is particularly true for industrial source nitrogen dioxide (NOX) emissions, which are the outcomes modeled in this study. Heckman Management Quality and Its Impact on Government Performance 5 Under the CAA, the ability of management to effectively achieve policy goals depends on good management practices, sufficient funding for environmental efforts, and political support that enables states to take the actions necessary to enforce environmental standards that negatively impact, or are perceived to negatively impact, economic output in a state and may be seen as overly intrusive policy interventions. Problem Tractability: The idea that the technology available to deal with the problem situation, the severity of the problem, and the desired change in the problem state will impact the effectiveness of any policy intervention. No policy can accomplish unrealistic goals that we do not have the knowledge or methods for achieving. Empirical Support for the MSIM Empirical analysis has typically supported the MSIM (Bullock 1981; Goodwin and Moen 1981; Lester and Bowman 1989; McFarlane 1989; Meier and McFarlane 1995; Sabatier and Klosterman 1981; Zheng 2000). However, these studies typically have not incorporated measures of all three types of factors in their analysis. Also, the impact of implementer skill or management quality has not been tested in prior research because a suitable measure was not available (Mazmanian and Sabatier 1989; McFarlane and Gruebel 2006). Additionally, implementation research has typically been limited in regards to the generalizable insights it has produced because such research often analyzes case studies of failures or disasters rather than conducting quantitative analyses of a large number of similar government entities implementing similar policies (Fox 1987; O’Toole 2000, 2004). This study provides generalizable results about factors affecting policy implementation by analyzing nearly all the American states’ implementation of air pollution policy and incorporating state-level measures for all the major categories defined in the MSIM, including management quality. The GPP Management Measure According to Ingraham, Joyce, and Donahue (2003), the GPP grading process is ‘‘the largest and most systematic effort to define and measure good management using rigorous and consistent techniques.’’ The GPP grades are used by public administration scholars, policy makers, and the media as indicators of state management quality because they are based upon transparent, concrete, and detailed criteria developed by expert panels comprised of academics and practitioners from all levels of government (Borins 2005; Clifton 2000; Coggburn and Schneider 2003; Donahue, Selden, and Ingraham 2000; Lewis 2005). The original GPP criteria for each management system are summarized in Table 1. The management systems presented in Table 1 were selected ‘‘because they were judged to be common systems in all levels of government, they have common characteristics that are amenable to comparison, and they compromise a major part of government Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 In this context, states vary widely on both the level of industrial NOX pollution they face and the extent of change required for bringing them into compliance with the CAA standards. The technology and techniques for reducing air pollution are available and well understood, so the level of industrial output is the major difference in problem tractability between states that will impact industrial NOX emissions and each state’s ability to reduce those emissions. 6 Journal of Public Administration Research and Theory Table 1 GPP Criteria for Assessing State Management Quality Management System Financial Human Resources Capital Infrastructure Managing for Results Source: Adapted from GPP (2002, Appendix E). managers’ and organizations’ management activities’’ (GPP 2002). The criteria represent a synthesis of academic research and measure the application of general management principles that can be accomplished using different practices, depending on the context (e.g., Williams 2005). Overall, the GPP criteria emphasize rational decision making, operational transparency, public accountability, and formal planning for and monitoring of the performance of each management system. According to the GPP, sustained, long-term performance at a high level requires effective maintenance, ongoing coordination, continual monitoring, and timely improvement to the management systems. The final GPP evaluation relies primarily on three main data sources: (a) a management survey completed by each state, (b) documents about each state’s management systems (e.g., budget documents, strategic plans, and human resources policies and procedures), and (c) interviews conducted with state government officials and external stakeholders, such as reporters and representatives from citizen watchdog groups. The GPP graders obtain and review similar documents and interview people in similar positions within each state to maximize the comparability of the information obtained and enable Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Information Technology Quality Criteria/Principles Multiyear perspective on budgeting Mechanisms in place that preserve fiscal stability and health Sufficient financial information available to policy makers, managers, and citizens Appropriate control over financial operations Conduct strategic analysis of present and future HR needs Able to obtain necessary employees Able to maintain an appropriately skilled workforce Able to motivate employees to perform effectively in support of goals Civil structure supports ability to achieve workforce goals Provide information that supports managers’ needs and strategic goals Systems form a coherent structure Conduct meaningful, multiyear planning Perform adequate training Can evaluate and validate return on investments Can procure necessary systems in a timely manner Systems support the ability to communicate with and serve citizens Conduct thorough analysis of future needs Monitor and evaluate projects during implementation Conduct appropriate asset maintenance Engage in results-oriented strategic planning Develop indicators and evaluative data to measure progress toward accomplishments and results Use data for policy making, management, and progress evaluation Clearly communicate results to stakeholders Heckman Management Quality and Its Impact on Government Performance 7 an assessment on all the criteria (Ingraham, Joyce, and Kneedler 2003; N. Johnson, personal communication, April 22, 2010).2 The final grades are based on an assessment of the management survey responses and documentary evidence by academic experts and an assessment of the interview responses by the journalists who conduct the interviews. In both cases, multiple academics and journalists individually review the data and assign grades for each state. Then, a team of the academics and a team of the journalists separately agree on a grade for each state. Finally, the academic and journalistic groups collaborate to arrive at a final grade. The approach used to assign the GPP grades seems sound given the ambitious and complicated nature of assigning management quality grades to all fifty states (Borins 2005; N. Johnson, personal communication, April 22, 2010). Studies using the GPP have typically found the expected relationships with other management quality measures and government performance variables. The GPP has been found to be related to another measure of management quality (Burke and Wright 2002), to various measures of state quality of life (Coggburn and Schneider 2003), to certain measures of social capital (Knack 2002), and to local government human resources effectiveness (Donahue, Selden, and Ingraham 2000). This study uses the overall state GPP grades, instead of the management system grades, to focus the analysis on the GPP as a holistic measure of management quality. Also, the management system grades for each year are not comparable for all the years included in this analysis because the management system categories were consolidated after 2001 from the five presented in Table 1 to four—Money, People, Infrastructure, and Information. However, the GPP still applied similar criteria, followed a similar grading process, and reviewed substantially the same evidence in assigning the overall grades used in this study. The 2005 changes to the GPP present a challenge for comparing the subcategory grades to past grades but are only of minimal concern when comparing the overall grades to each other (Pew Center for the Sates, 2008; N. Johnson, personal communication, April 22, 2010).3 METHODS, DATA, AND HYPOTHESES The foundation for my empirical examination is a regression analysis, using a model specification based upon the MSIM, to analyze the impact of management quality and other key state-level factors on two different measures of state industrial NOX emissions. Modeling different dependent variables determined by the same causal factors facilitates comparative analysis of the two models’ regression results, including some assessment of the robustness of the empirical findings (Pawson 1989). More detailed information on the grading process can be found at http://www.governing.com/gpp/index.htm, http:// www.pewcenteronthestates.org/initiatives_detail.aspx?initiativeID536072, and in Ammar, Wright, and Selden (2000). 3 There is a Pearson correlation of .84 between the 1999 and 2001 overall grades and correlation of .81 between the 2001 and 2005 overall grades, suggesting relative stability and continuity in the overall grades over time. 2 Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Empirical Studies Using the GPP 8 Journal of Public Administration Research and Theory 4 A similar program was initiated in the late 1990s for NOX emissions trading, but the implementation was too late to impact the outcomes examined in this analysis. Also, the program focused primarily on NOX emissions from electric utilities, which are excluded from this analysis. 5 External assessments of the EPA’s effort to measure the costs and benefits of the CAA have not questioned the accuracy of its emission estimates. However, scholars have criticized the projected costs and benefits resulting from these estimated emissions reductions (see Freeman 2002, Lutter and Belzer 2000, and Portney 2000). Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Industrial NOX emissions, excluding emissions from power plants, are analyzed because these pollution levels are most likely to be impacted by state implementation efforts. In contrast, pollutants, such as sulfur dioxide, are more likely to be affected by federal cap and trade programs and utility regulation.4 Similarly, mobile source pollutants are mostly affected by federal enforcement of national regulations, such as compliance with automobile fuel efficiency standards. Focusing on industrial NOX emissions also minimizes the problem of cross-state pollution affecting the findings (USEPA 2001). Therefore, analyzing NOX industrial point source emissions should provide the most favorable context for discerning the impact of state-level factors on these air pollution control outcomes. Additionally, NOX pollution is an important policy problem because it negatively impacts public health by contributing to the formation of ozone and particulate matter. Reducing ozone levels and particulate matter was a priority of the 1990 CAA because of the severity of the problems caused by these pollutants (USEPA 1999). The first dependent variable is tons of industrial point source NOX emissions per state. An aggregate emissions measure such as this, often standardized by population or some other factor, is one of the most common air pollution control outcome measures used in this type of analysis (e.g., Carson, Jeon, and McCubbin 1997; Lowry 1992; Stern 1998). Table 2, which presents the descriptive statistics for the dependent and independent variables, shows that most states produce industrial, point-source NOX emissions of less than 115,000 tons. Also, the distribution of NOX emissions is skewed above the mean, so the log of the emission variable is used in the analysis to bring the distribution close to normal, which helps to ensure more accurate coefficient estimates (Stern 1998). Although an aggregate emissions measure is a commonly used dependent variable in analyses examining state and national environmental performance, such variables are not necessarily the best measure of the policy goals because environmental policy is ultimately focused on reducing emissions. Therefore, a change in emissions measure is a better outcome variable to use when analyzing the impacts of pollution control efforts because it better reflects policy goals (Ringquist 1993). To address this issue, the second dependent variable is emissions reductions per state as a result of the 1990 CAA Amendments (ERNE). This variable measures the estimated reductions in state-level emissions between 1990 and 2000 after the CAA was amended in 1990. The 1990 CAA law required the USEPA to issues a series of reports on the costs and benefits of the policy (USEPA 1997). The second of these reports was issued in 1999 and estimated the national impact of the 1990 CAA Amendments on pollution emission between the years 1990 and 2000. These estimates are the foundation for deriving the second dependent variable used in this study.5 In the report on the benefits and costs of the 1990 CAA Amendments, the USEPA (1999) forecasted pollutant emission levels for NOX emissions under two scenarios. Heckman Management Quality and Its Impact on Government Performance 9 Table 2 Descriptive Statistics for Model Variables Variable Mean SD Minimum Maximum 2.6 0.5 1.0 3.7 50 15 15 86 0.14 2.20 0.00 0.96 $26.1 $7.3 $2.1 $594.2 $27,802 $30,712 $628 $169,395 $7,824 $13,093 $22,837 $77,615 51,918 61,789 386 452,007 25,453 26,148 278,344 45,221 One scenario assumed that the CAA Amendments were not passed in 1990 and that no additional control requirements would be passed by the national, state, or local governments between 1990 and 2010. The second scenario estimated emissions based on the forecasted impact of the CAA with the 1990 Amendments. In short, USEPA estimated the impact of the actual policy and the impact under the counterfactual. I used the USEPA emission estimates and actual data on NOX industrial point source emissions for the years 1990 and 2001 to calculate each state’s reduction in emissions as a result of the CAA. A key assumption of the ERNE calculation is that the each state’s relative share of national emissions in 1990 would remain the same if more stringent standards and enforcement mechanisms had not been introduced by the 1990 CAA Amendments. Based on this assumption, the actual 1990 relative shares can be used to apportion the USEPA national projection for 2000 under the non-CAA Amendments scenario. Similarly, each state’s share of actual 2001 emissions is used to apportion out its share of the USEPA NOX emissions projections for industrial point sources in 2000 under the CAA Amendments scenario.6 As shown in Table 2, most states were estimated to have reduced NOX industrial emissions by less than 21,000 tons. Five states were projected to have had increases in NOX emissions after implementation of the 1990 CAA Amendments—Arkansas, Georgia, Hawaii, Kentucky, and Mississippi. The distribution of the ERNE variable is approximately normal, so no transformation of this variable was necessary. The dependent variables are not standardized by state population or some other factor because it is the aggregate pollution levels that are of concern for public officials. It is the 6 More detail on the ERNE calculation and an example state calculation is presented in Appendix 2. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Nonstatutory GPP Management Grade (1999, 2001, 2005) Level of Citizen Liberal Ideology (1999, 2001, 2004) Environmental Interest Group Influence (1999–2000, 2000–01, 2003–04) Statutory Air Pollution Control Spending (in millions) (1999, 2001, 2004) Problem Tractability Real Manufacturing GDP (in millions) (1999, 2001, 2004) Increase in Value of Manufacturing GDP from 1990 to 2000 (in millions) Dependent NOX Emissions (in tons) (2000, 2002, 2005) Estimated Reduction in NOX Emissions 10 Journal of Public Administration Research and Theory Table 3 Model Variables, Research Hypotheses, and Data Sources Variable Lag of Dependent Variable Data Source Negative http://www.pewcenteronthestates.org Negative Negative Berry et al. (1998) http://www.followthemoney.org Negative Author’s original data collection and Environmental Council of the States Positive http://www.bea.gov/regional/gsp/ Negative http://www.bea.gov/regional/gsp/ Positive in AE Model Negative in ERNE Model USEPA National Emissions Inventory, http://epa.gov/airdata/neidb.html Note: AE, Aggregate Emission model. overall levels that create the health and safety impact and the goal of policy is to reduce aggregate levels of pollutants not per capita reductions. However, the analysis does account for size effects on the dependent variables by including a lag of the dependent variable in the model for each outcome measure. I mitigate simultaneity issues in the emissions model analysis by using prior years’ values for all the independent variables, which should produce more accurate coefficient estimates. Simultaneity is not a concern with the ERNE model because it is a measure of change (Ringquist 1993; Stern 1998). Causal Variables and Expected Relationships Table 3 shows the independent variables used in the analysis and the hypothesized relationships with the dependent variables. Nonstatutory Variables 1) The GPP grades are used to measure management quality. As shown in Table 2, almost all states have C-level management or better, according to the GPP grades. The average GPP grade is 2.6 or just below a B-level. The grade distribution is essentially bimodal with 95% of states rating a B-level (26 states) or C-level (21 states) grade. GPP Hypotheses: The GPP variable should have a negative relationship with both emissions levels and the ERNE because states with better management quality should have Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Nonstatutory GPP Management Quality Grade Citizen Ideology Index Environmental Interest Group Influence Statutory Air Pollution Control Spending Problem Tractability Real Value of State Manufacturing GDP (AE model) Change in Value of State Manufacturing GDP (ERNE model) Expected Relationship with Dependent Variables Heckman Management Quality and Its Impact on Government Performance 11 lower emissions and achieve larger reductions, which are measured by larger negative values. 2) A state-level citizen ideology index developed by Berry et al. (1998) is used to capture the concept of citizen support for CAA implementation.7 The index determines how liberal citizens are in each state by calculating the ideology of each state’s Congresspeople based upon ratings from the liberal group Americans for Democratic Action and the conservative group Americans for Constitutional Action. The ideology index can range from 0 (extremely conservative) to 100 (extremely liberal). 3) The MSIM concept of interest group support is captured with a measure of environmental interest group influence. The variable is the proportion of pro-environmental interest group campaign contributions to successful state-level candidates relative to total interest group campaign contributions to successful candidates from both pro-environmental and promanufacturing industry groups. The larger the value of the spending ratio variable the more influential environmental interest groups are in the state relative to industry interests. This is a better measure of the actual relative influence of interest groups than prior studies, which have typically only examined potential influence of environmental groups based upon state membership in certain environmental groups (Lester 1995). Table 2 shows that environmental interest groups are not very influential relative to industry groups, although there is wide variation across states. Environmental groups’ contributions to winning state-level candidates represented an average of only 14% relative to total campaign contributions made during the three election cycles used in the analysis. In most states, environmental contributions did not exceed 34% of total contributions. Interest Group Hypotheses: States with relatively more influential pro-environment interest groups should achieve lower emission levels and greater emission reductions, so this variable should have a negative relationship with both dependent variables. 7 Berry et al. reported on the measure in 1998 and subsequently made available updated measures for states through the year 2004 in the revised 1960–2004 citizen ideology series. Details on the derivation of the ideology index and the updated figures used here can be found at http://www.icpsr.umich.edu/icpsrweb/ICPSR/. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Berry et al. have demonstrated the reliability and validity of the measure through empirical testing of many of the assumptions upon which the measure is based and testing expected relationships with other relevant phenomenon. This variable avoids the pitfall of measures commonly used in implementation research that merely quantify the partisan composition of state or national officials as a measure of state ideology (e.g., Lester et al. 1983). This is problematic because the meaning of partisan ideology is not consistent across states (Berry et al. 1998). For example, Democrats in Texas are more likely to be ideologically similar to Republicans in Massachusetts rather than Democrats. As shown in Table 2, states are, on average, somewhat moderate ideologically with a mean of 47 out of a possible 100 on the ideology index. Nearly 60% of states have a score in the 40s or 50s. Citizen Ideology Hypotheses: More liberal state populations are expected to demand more stringent environmental enforcement, and so there should be a negative relationship between the citizen ideology variable and the dependent variables. 12 Journal of Public Administration Research and Theory Statutory Resources Variable Problem Tractability Variables The model includes two problem tractability variables. The first variable is a measure of the value of each state’s manufacturing gross domestic product (GDP). The value of production in the manufacturing sector in each state should have a direct impact on emission levels and reductions that can be achieved. In the aggregate emissions model, the variable is the total real value of each state’s manufacturing GDP. In the ERNE models, the manufacturing GDP variable is the change in manufacturing value between 1990 and 2000. The second variable is a lag measure of the dependent variable, which also captures the extent of each state’s pollution problem. In the emissions model, the variable is tons of NOX emissions from the prior year, and in the ERNE model, it is the tons of NOX emissions in each state in 1990. The lag measures should help account for size effects that can explain variation arising from the use of the aggregated dependent variables. With all of the problem tractability variables, the aggregate levels of manufacturing output are used, rather than standardizing by population or some other basis, because it is the total amounts that create the negative environmental impacts. Two-thirds of states having manufacturing output valued at less than $60 billion. The average increase in manufacturing GDP is more than $7.8 billion with two thirds of states generating less than $21 billion in increased manufacturing output. Manufacturing Output Hypotheses: More manufacturing should mean higher emissions, and so there should be a positive relationship with state emissions levels. The greater the increase in manufacturing, the more difficult it would be to reduce emissions. Therefore, manufacturing GDP should have a positive relationship the ERNE variable. Lag Variables Hypotheses: The prior year emissions lag measure should have a positive relationship with the aggregate emissions outcome variable, but the ERNE outcome 8 Appendix 3 provides more detail on the process used to collect the spending data used in this analysis. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Total state spending on air pollution control activities is included as a measure of the financial resources used to achieve policy goals.8 An aggregate measure of spending, rather than a per capita measure, is used because aggregate spending is a better measure of capacity. Following the logic of Ringquist (1993), pollution control is an ‘‘aggregate problem’’ that requires a certain minimum level of spending to effectively generate results, regardless of the amount of pollution to be reduced. It is the absolute level of spending that best captures the fiscal capacity of a state to carry out the activities required to effectively reduce pollution rather than some standardized measure such as spending per capita. For example, a small state may have quite high per capita spending, but its overall spending may not provide sufficient capacity to carry out an effective enforcement program. States that spend more on air pollution control should have higher capacity to implement the CAA and achieve greater emission reductions. Table 2 shows that within each state, an average of more than $26 million is spent on air pollution control with two thirds of states spending more than $18.5 million and less than $33.5 million. Spending Hypotheses: The air quality spending variable should have a negative relationship with both dependent variables. Heckman Management Quality and Its Impact on Government Performance 13 measure should have a negative relationship with the lag measure because states starting with higher levels of emissions in 1990 should be able to achieve greater reductions.9 FINDINGS AND ANALYSIS Table 4 presents the results of the regression analysis with the log of NOX emissions as the dependent variable and Table 5 shows the results of the regression analyses with the ERNE measure as the dependent variable.10 Management Quality and Other Nonstatutory Variables Table 4 Regression Results with Log of Industrial Source NOX Emissions as Dependent Variable (Panel Data for Years 2000, 2002, and 2005) Independent Variable Nonstatutory GPP Grade Level of Citizen Liberal Ideology Environmental Interest Group Influence Statutory Air Pollution Control Spending Problem Tractability Value of State Manufacturing Lag of Aggregate NOX Emissions Other 2002 Dummy Variable 2005 Dummy Variable Constant Model Statistics Coefficient SE p Value 2.008 2.026 0.13 0.01 .95 .00 .022 2.35 .95 0.00 .02 0.00 0.00 .00 .00 0.16 0.16 0.43 .36 .55 .00 2.000000004 .00002 .000008 2.149 2.097 10.78 Adjusted R2 5 .62 N 5 141 Note: All F tests were significant at 99% confidence level. The models also include dummy variables for relevant years to account for temporal effects. The NOX emission analysis was also performed using per capita measures to control for differences in population. The direction and magnitude of the GPP coefficient was similar in these models; however, the coefficient sign for citizen ideology, spending, and the value of manufacturing was the opposite of these results. Accounting for a change in population in the ERNE analysis produced similar results to those presented here. 11 The importance of statistical significance is debatable here since the data represent almost the entire population rather than a sample. As a result, the analysis focuses on direction and magnitude of the variables and less on statistical significance. However, variable p values are presented and discussed to allow readers to make their own judgment. 9 10 Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 In both the aggregate emissions model and ERNE Model 1, the GPP management grade has the expected relationship with emissions but is not statistically significant.11 However, there is a notable difference in the magnitudes of the GPP coefficients between the two models. Even if one ignores the lack of statistical significance, the GPP coefficient in the aggregate NOX emissions model is close to zero, suggesting no substantive impact on overall emissions. In contrast, the GPP coefficient in the ERNE Model 1 indicates 14 Journal of Public Administration Research and Theory Table 5 Regression Results with Dependent Variable of Projected Emission Reductions for Industrial Source NOX Emissions from 1990 to 2000 Attributable to the 1990 CAA Amendments Independent Variable Model Statistics SE p Value Model 2 SE 27,743 2550 4,968 212 .13 .01 213,495 2608 6,106 211 .03 .01 214,067 15,563 .37 214,496 15,289 .35 2.0000000003 0.00 .04 2.0000000009 .00 .05 .60 0.49 .23 .57 .49 .24 2.19 0.04 .00 2.24 .05 .00 — — .0000000003 .00 .13 19,443 .01 72,872 20,176 .00 — 53,145 2 Adjusted R 5 .52 N 5 47 p Value 2 Adjusted R 5 .53 N 5 47 Note: All F-tests were significant at 99% confidence level. a substantive impact of management quality on the level of emission reductions achieved. The GPP coefficient in Model 1 is nearly 15% of the mean NOX emissions, suggesting a substantive impact of management quality on the emission reduction outcomes. The citizen ideology coefficient is statistically significant and has the expected negative relationship with emissions in both the aggregate emissions model and ERNE Model 1; however, the magnitude of the coefficient is notably different in the two models. A one-point increase in the citizen ideology measure is associated with a .02% decrease in NOX emissions. This means that a 10-point increase in the ideology index (10% on the 100-point scale) would be associated with a 2% decrease in NOX emissions. The ideology coefficient magnitude in the ERNE model is notably greater at about 1% of the mean of total NOX emissions. Therefore, a 10-point increase in the citizen ideology index would be associated with a reduction equivalent to 10% of total NOX emissions. This indicates a substantive difference between the two variables’ impacts on emissions. The coefficient for the interest group influence measure is positive and not statistically significant in the emissions model but is negative and statistically significant in ERNE Model 1. Additionally, there is a notable difference in the magnitude of the interest group influence coefficient between the two models. Even if one ignores the lack of Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Nonstatutory GPP Grade Citizen Liberal Ideology Environmental Interest Group Influence Statutory Air Pollution Control Spending Problem Tractability Change in State Manufacturing Value NOX Emissions (1990) Other Management  Spending Per Capita Constant Model 1 Heckman Management Quality and Its Impact on Government Performance 15 statistical significance, the interest group coefficient in the aggregate NOX emissions model is close to zero, suggesting no substantive impact on overall emissions. Conversely, a 10% increase in interest group influence is associated with an emission reduction equal to more than 25% of the mean in aggregate emissions. One plausible explanation for the difference in the coefficient sign between the two models (ignoring the lack of statistical significance) is that pro-environment interest groups are stronger in states with worse emission problems, but they influence states to make greater NOX pollution reductions. Lastly, the coefficient of the interest group influence variable in the ERNE Model 1 is nearly double the magnitude of the GPP coefficient, suggesting politics affect outcomes more than management. The spending coefficient is statistically significant and has the expected negative relationship with both outcome measures. However, the impact of spending is modest or negligible in both the aggregate emissions model and ERNE Model 1. A 1 standard deviation increase in spending is associated with a 3% lower level of NOX emissions and a 0.02% reduction in emission levels. One plausible explanation for the limited impact of spending increases is that the federal government policy design and USEPA oversight causes states to spend at high enough levels that spending differences between states have negligible impact on pollution outcomes. Another plausible explanation for the negligible impact of spending is that higher spending by itself does not reduce emissions. Researchers such as Boyne (2003) have theorized that spending must be coupled with good management to have a substantive and positive impact on performance. I examined this possibility by including a management-spending interaction variable in the ERNE model. The interaction variable is calculated by multiplying the GPP and air quality spending per capita for each state, therefore weighting spending more heavily when it is done in well-managed states. As shown in Table 5, the management-spending interaction variable is significant, associated with greater emissions, but has a negligible impact on emissions based upon the magnitude of the coefficient. The inclusion of the management-spending interaction variable also does not impact the total variation explained relative to ERNE Model 1 and does not have any notable impact on the citizen ideology, the environmental interest group influence or the problem tractability variables, nor on the signs of the spending and GPP coefficients. However, the magnitude of the spending coefficient in Model 2 is three times greater than in Model 1, though the impact is still quite modest. Most interesting is the impact on the significance and magnitude of the GPP coefficient as a result of including the management-spending interaction variable. The GPP measure is not statistically significant in Model 1, but it is significant in Model 2 and the magnitude of the coefficient is nearly double that of the GPP coefficient in Model 1. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Statutory Resources—Spending 16 Journal of Public Administration Research and Theory Problem Tractability The problem tractability variables have the expected relationship with NOX emissions in all the models; however, problem tractability is not statistically significant in the ERNE models. Nonetheless, the magnitude of the coefficients in all the models is quite small, suggesting a negligible impact of problem tractability on these outcome measures. This is not too surprising given that the methods for reducing pollution from industrial point sources are well understood and the technology for doing so is also readily available. Therefore, the problem is quite tractable and achieving policy goals is technically feasible, but whether the methods will be applied and the technology used effectively depend largely upon good management and the financial and political support for implementation. Overall, the findings indicate a consistent yet modest impact of citizen ideology and air pollution control spending on NOX emissions. More liberal citizens and more spending seem to contribute to modestly lower NOX emissions and greater reductions in emissions under the CAA. The problem tractability variables were not consistently significant and their impact was negligible in all models based upon the coefficient magnitudes. This suggests that problem tractability is not a major factor in determining these outcomes. How one interprets the impact of management quality and environmental interest group influence variables depends, in large part, on one’s views on the importance of the statistical significance of the variables, the proper model specification, and the best outcome measure. If statistical significance is critical, then neither management quality nor interest group influence help explain NOX emission outcomes, except that management quality is significant and has a substantive impact if the best model specification is ERNE Model 2. This change in significance and magnitude suggests that analyses designed to examine relationship between management and performance may need to account for the interaction of management quality and spending. The ERNE Model 2 would seem to be the best model because it includes both the best outcome measure and the management-spending interaction variable, which captures the critical insight that good management is required to make effective use of available financial resources (Boyne 2003). Similarly, if one is not concerned about statistical significance and considers the ERNE variable to be a better measure of the policy outcomes sought, then environmental interest groups appear to a have a rather substantive impact on the ability to achieve emission reductions in a state. Otherwise, interest groups seem to have little or no impact on NOX emissions. RESEARCH AND POLICY IMPLICATIONS The specific findings of this analysis have broader research and policy implications when examined within the context of prior research into public management and government performance, particularly if one emphasizes the results arising from the comparative analysis of the ERNE models. These findings have notable implications for public administration research and policy. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Summary of the Regression Results Heckman Management Quality and Its Impact on Government Performance 17 Good Management and Government Performance Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 The findings of this analysis add to the management, government performance, and implementation literature that provide evidence that management quality and the political environment have a substantive impact on government performance outcomes (e.g., Boyne 2003; Boyne et al. 2005; Lester and Bowman 1989). The impact of management on performance outcomes is important and can exceed the impact of spending and the constraints created by the severity of the problem. Political factors such as citizen ideology and interest group influence seem to have an even greater impact on performance outcomes than management quality. Still, improving management is a viable strategy for practitioners and policy makers seeking to improve government performance. Because this analysis used the GPP grades as the measure of management quality, the study also sheds light on the management practices that constitute good management. The GPP criteria define relatively specific practices that constitute good management including rational decision making, operational transparency, public accountability, and formal planning for and monitoring of the performance of each management system. This transparent and concrete definition of management should be helpful to policy makers and practitioners seeking to improve public management. Additionally, the detailed and transparent nature of the GPP measure can facilitate useful dialogue about the nature of good management, which can improve both research and practice. Whatever one thinks of the validity of the GPP, measures like it provide a starting point for professional dialogue about how to define and measure good management. Discussions about what exactly constitutes good management practice should help scholars to better understand the impact of management and help practitioners be more reflective professionals. The result should be management research that makes a more practical contribution to improving management practice and government performance. Although the GPP is a promising measure, it has limitations that relate to the key limitations of this study. First, the practical guidance based on this study is not as specific as it could have been if the GPP subsystem grades had been able to be incorporated in the study. Certainly, a subsystem analysis would be worthwhile in future research. More fundamentally, some inconsistencies in the empirical findings in this study may, in part, be explained by the limitations of the GPP as a measure management quality. The GPP is primarily a measure of management capacity, and it does not effectively capture the other major aspect of management as defined in the literature—the quality of the daily execution of policy by states and the execution of agency-level policies within the state environmental agencies (Kotter 1990, Mintzberg 1975; Tsoukas 1994). However, the inability to account for execution is not limited to the GPP or this study, but is one of the fundamental obstacles to developing any quantitative measure of management quality that seeks to define good management practice. Developing formalized policies, procedures, and structures is the part of good management practice that can be relatively easily observed and evaluated in retrospect, but determining how well structures are utilized, policies are carried out, and procedures are executed is not amenable to after-the-fact examination. This challenge suggests both opportunities for improving the measurement of management quality and limitations on such quantification efforts. The GPP project and other scholarly efforts to quantify management quality need to better account for 18 Journal of Public Administration Research and Theory management execution in order to develop better measures and a better understanding of the management-performance connection. However, because management execution is action oriented, communication based, and ephemeral, there are limits to our ability to measure and quantify it (Kotter 1990; Mintzberg 1975; Sull and Spinosa 2007). As such, the study of management execution is more conducive to qualitative research approaches that rely on direct observation and interpretation rather than on after-the-fact quantification using formal documents or secondary data. Therefore, a mixed-methods approach may be the best way to understand good management and its impact on performance (O’Toole 2004). Analyzing Government Performance Accounting for Management-Spending Interaction Boyne (2003) has detailed the contradictory findings in the government performance literature as to the impact of spending on performance and concluded that this discrepancy may be a result of differences in measurement. Specifically, some studies operationalize resources using aggregate measures of spending while others examine real resources actually used to carry out activities designed to achieve outcomes (e.g. people and equipment). Boyne theorizes that spending variables measure financial capacity, which does not directly determine results. Instead, variables that measure real resources capture the actual use of that financial capacity, which should directly impact outcomes. This study provided evidence for Boyne’s claim by including in one of the model specifications a management-spending interaction variable to account for the notion that it is the financial capacity available for achieving a policy goal and how effectively these resources are used that determines performance outcomes. This model produced results most aligned with the MSIM hypotheses and other studies into the impact of management on performance outcomes. Selecting Outcome Measures The findings of this study were also notably impacted by the selection of the outcome measure. For example, the model that used aggregate pollution levels as the measure of performance outcomes did not show a significant or substantive impact of management quality on pollution. Conversely, the model that used the estimated reduction in pollution emissions as the performance outcome measure did show substantive impact of management on performance. This result may suggest that the study findings are unreliable, but I contend that they illustrate the misleading findings that can result from selecting an outcome measure not closely related to policy goals. For example, studies seeking to explain the impact of policy and politics on pollution have often measured performance outcomes using a per capita Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 This study also provides insights into how different measures and model specifications may help explain the contradictory findings often found in public administration research into the causes of government performance (Boyne 2003). For example, this analysis provided evidence that inclusion of a management-spending interaction variable and the selection of the performance outcome measure have a notable effect on the empirical findings. Heckman Management Quality and Its Impact on Government Performance 19 emissions variable. However, governments are not trying to reduce per capita emissions but seek to reduce total pollution from existing levels (Ringquist 1993). Therefore, a measure of pollution reduction outcomes better captures the goals of air pollution control efforts. In this study, the model using the emissions reductions achieved as a result of national air pollution policy produced results more in line with theory and other studies into the impact of management on performance outcomes. This finding supports the notion that better outcome measures produce more accurate results. Applying a Comparative Approach CONCLUSION This study incorporated three key elements: (1) a management quality measure based upon criteria that clearly define good management practice, (2) a performance outcome measure that accurately captured policy goals, and (3) a comparative analytical approach based upon two different outcome measures that should be impacted by the same causal factors. Together, these elements shed new light on the management-performance connection and the causal factors affecting policy outcomes. For example, the comparative analysis illustrated the importance of accounting for the interaction of management and spending when modeling government performance outcomes. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 The findings discussed above were arrived at by conducting a comparative analysis using two different performance outcomes that were expected to be impacted by the same causal factors. The comparative approach facilitated an assessment, albeit limited, of the robustness of empirical findings and produced inconsistencies and discrepancies in the empirical results, which spurred additional questions and analysis (Pawson 1989). For instance, the citizen ideology and spending variables were consistent across all models in terms of their sign, statistical significance, and magnitude. This provides a high level of confidence in the findings related to these variables. Conversely, inconsistent results in the statistical significance, direction, or magnitude of other variables’ coefficients raised questions that required explanation or additional analysis. For example, interest group influence was associated with higher overall emission levels but also greater reductions in emissions. This discrepancy demanded an explanation and spurred the insight that pro-environmental interest groups become more influential in states with more severe pollution problems, and in turn, these groups are more effective at causing reductions in emissions. This insight could not have been produced by an analysis that modeled emissions as the only outcome variable. Instead such an analysis would have suggested an opposite finding—stronger pro-environment groups are ineffectual because they are associated with higher emission levels. In fact, this is not an uncommon finding in studies looking at the effect of interest groups on policy outcomes (e.g., Lester and Bowman 1989). Overall, these examples illustrate how applying a comparative approach can improve public administration research by providing a way to assess the robustness of empirical findings and by generating discrepancies that spur additional analysis. In this case, the result was a clearer and more sophisticated understanding of the causal factors and relationships that affect government performance. 20 Journal of Public Administration Research and Theory The study also examined the benefits that can be gained by including these elements in public management and government performance research. For example, using management measures that are based upon assessments of clearly defined management practices should produce more accurate and useful research results. Additionally, developing measures based upon transparent and concrete criteria will facilitate constructive dialogue about what constitutes good management practice and inform academics’ and practitioners’ endeavors. In short, future research could benefit from building upon the types of measures and methods used in this study because such research would generate more accurate and practical insights into good management practice and its impact on policy implementation outcomes. Trevor Brown at the Ohio State University Glenn School of Public Affairs. Appendix 1 Amendments enacted in 1990 to Titles I, V, and VII of the CAA enhanced the responsibility and authority of states to reduce air pollution from industrial point sources (McCarthy, et al. 2007). Changes most relevant for this analysis include: 1. All states had to develop implementation plans for meeting air pollution standards both in areas in nonattainment with the USEPA standards and for preventing significant deterioration of air quality in areas that were in attainment. New classifications were created for metropolitan areas deemed to be in ‘‘nonattainment’’ with one or more air quality standards, and states’ implementation plans were required to outline strategies for bringing such areas into attainment within specific time frames established by the law. 2. In nonattainment areas, new facilities and major modifications to existing facilities were only to be approved by states if offsetting emission reductions could be achieved. 3. All major air pollution sources, and certain nonmajor sources in nonattainment areas, were required to obtain annual operating permits that specified the level and type of pollutants a source may emit. States were charged with implementing the permit program including monitoring and enforcing compliance with permit requirements. 4. Penalties for purposeful violations of the CAA were increased, a grace period for ceasing violations without penalties was removed, and environmental agencies were authorized to assess administrative penalties. Appendix 2 The basic formula used by the USEPA to forecast the impact of the 1990 CAA Amendments on pollution levels was 2000 NOX Emissions 5 1990 Industrial Point Source NOX Emissions  Economic Growth Factor  Pollution Reduction Factor. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 FUNDING Heckman Management Quality and Its Impact on Government Performance 21 Both scenarios employed an economic growth factor that is based upon federal government projections of the growth in production from each industrial facility and growth in state populations. The projections assumed that the geographic distribution of population and economic activity would be the same under both scenarios. The USEPA also estimated total national NOX emissions in a counterfactual scenario in which all national and state policies in existence prior to the 1990 CAA Amendments remained unchanged (the non-1990 CAA Amendments projection). An example calculation of the ERNE for Pennsylvania is presented below to illustrate how this variable was derived for each state: 1. Pennsylvania’s Estimated 2000 Emissions without the 1990 CAA Amendments: B. Actual 1990 national industrial NOX emissions = 3,157,647 tons C. Pennsylvania’s share of actual 1990 industrial NOX emissions = 188,599 tons or 6.0% D. Estimated emissions in year 2000 without CAAA: 3,173,300  .06 = 190,398 2. State’s Estimated 2000 Emissions with 1990 CAA Amendments: A. USEPA national NOX emissions estimate for year 2000 with CAAA = 2,060,400 tons B. Actual 2001 national industrial NOX emissions = 2,959,829 tons C. Pennsylvania’s share of actual 2001 emissions = 114,888 tons or 3.8% D. Estimated emissions in year 2000 with CAAA: 2,060,400  .038 = 78,295 3. Pennsylvania’s ERNE: 78,295 2 190,398 = 2112,103 Appendix 3 The total air quality spending figure includes spending within a state by both state and local agencies using revenue from all sources (i.e., national, state, and local). Local agencies in 27 states have significant CAA enforcement responsibilities that have been delegated to them by the state or directly by the USEPA. I collected data for the air quality spending measure from different sources depending upon the state and local air agency. Initially, state and local Web sites were reviewed for annual reports from the state environmental agency and relevant budget and financial documents. When these documents did not provide the necessary data or the data did not clearly break out air pollution control spending, the author, with some assistance from NACAA, contacted officials in the state or local environmental agency and relevant budget agencies to obtain spending data or clarifications regarding published data. Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 A. USEPA national NOX emissions estimate for year 2000 without CAAA = 3,173,300 tons 22 Journal of Public Administration Research and Theory For a few states, I also relied on spending data from the Environmental Council of the States after assessing its likely accuracy. In some cases, data for a particular year had to be estimated, based upon historical data and historical rates of growth in air quality spending, because I could not obtain actual figures. Ultimately, the total state and local spending by state were determined for 47 states. Illinois, Montana, and New York are excluded from the analysis because data to calculate accurate air pollution control spending figures could not be obtained. REFERENCES Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Ammar, Salwa, Ronald Wright, and Sally Selden. 2000. Rating state financial management: A multilevel fuzzy-based system. Decision Sciences 31:449–81. Berry, William D., Evan J. Ringquist, Richard C. Fording, and Russell L. Hanson. 1998. Measuring citizen and government ideology in the American states, 1960–93. American Journal of Political Science 42:327–48. Borins, Sandford. 2005. Grading the graders. [Review of the book Government performance: Why management matters]. Journal of Public Administration Research and Theory 15 (3):463–66. Boyne, George A. 2003. Sources of public service improvement: A critical review and research agenda. Journal of Public Administration Research and Theory 13:367–94. ———. 2004. Explaining public service performance: Does management matter? Public Policy and Administration 19:100–17. Boyne, George A., Kenneth J. Meier, Laurence J. O’Toole, and Richard M. Walker. 2005. Where next? Research directions on performance in public organizations. Journal of Public Administration Research and Theory 15:633–39. Brown, R. Steven, and Valerie Green. 2001. State environmental agency contributions to enforcement and compliance. Environmental Council of the States. Brudney, Jeffrey L., Laurence J. O’Toole, and Hal G. Rainey. 2000. Chapter 14: Concluding perspectives. In Advancing public management: new developments in theory, methods, and practice, ed. Jeffrey L. Brudney, Laurence J. O’Toole Jr., and Hal G. Rainey, 235–52. Washington, DC: Georgetown Univ. Press. Bullock, Charles S. 1981. Implementation of the equal education opportunity act: A comparative analysis. In Effective policy implementation, ed. Daniel Mazmanian and Paul Sabatier. Lexington, MA: Lexington Books. Burke, Brendan F., and Deil S. Wright. 2002. Reassessing and reconciling reinvention in the American states: exploring state administrative performance. State and Local Government Review 34:7–19. Carson, Richard T., Yongil Jeon, and Donald R. McCubbin. 1997. The relationship between air pollution emissions and income: US data. Environment and Development Economics 2:433–50. Clifton, Diane B. 2000. AU outreach report challenges state government’s poor grade. Auburn University News, October 24. http://www.auburn.edu/administration/univrel/news/archive (accessed July 9, 2007). Coggburn, Jerrell D., and Saundra K. Schneider. 2003. The relationship between state government performance and quality of life. International Journal of Public Administration 26:1337–54. Donahue, Amy Kneedler. 2004. The influence of management on the cost of fire protection. Journal of Policy Analysis and Management 23:71–92. Donahue, Amy Kneedler., Sally Coleman Selden, and Patricia W. Ingraham. 2000. Measuring government management capacity: A comparative analysis of city human resources management systems. Journal of Public Administration Research and Theory 10:381–411. ECOS and USEPA. 1999. State environmental data in EPA’s National System. Washington, DC: ECOS and USEPA. Environmental Council of the States (ECOS). 2007. Delegation by environmental act. http://ecos.org/ section/states/enviro_actlist (accessed May 21, 2010). Heckman Management Quality and Its Impact on Government Performance Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Fox, Charles J. 1987. Biases in public policy implementation evaluation. Policy Studies Review 7:128–41. Freeman, Myrick, III. 2002. Environmental policy since earth day: What do we know about the benefits and costs? Agricultural and Resource Economics Review 31 (1): 1–14. Goodwin, Leonard, and Phyllis Moen. 1981. The evolution and implementation of family welfare policy. In Effective policy implementation, ed. Daniel Mazmanian and Paul Sabatier, 147–68. Lexington, MA: Lexington Books. Government Performance Project (GPP). 2002. Paths to performance in state and local government: A final assessment from the Maxwell School of Citizenship and Public Affairs. In ed. A. Colonna and J. Puma. Syracuse, NY: Campbell Public Affairs Institute. ———. 2005. State Grade Report. http://www.pewcenteronthestates.org/report_detail.aspx?id532742 (accessed October 22, 2007). Ingraham, Patricia W., Philip G. Joyce, and Amy E. Kneedler Donahue. 2003. Government performance: Why management matters. Baltimore, MD: Johns Hopkins Univ. Press. Knack, Stephen. 2002. Social capital and the quality of government: Evidence from the States. American Journal of Political Science 46:772–85. Kotter, John P. 1990. What leaders really do. Harvard Business Review 68:103–11. Lester, James P., 1995. Federalism and state environmental policy. In Environmental politics and policy: Theories and evidence, ed. James P. Lester, 39–60. Durham, NC: Duke Univ. Press. Lester, James P., and Ann O’M Bowman. 1989. Implementing environmental policy in a federal system: A test of the Sabatier-Mazmanian model. Polity 21:731–53. Lester, James P., James L. Franke, Ann O’M Bowman, and Kenneth W. Kramer. 1983. Hazardous waste, politics, and public policy: A comparative state analysis. Western Political Quarterly 36:257–85. Lewis, Bob. 2005. Virginia gets nation’s top grade in management. WTOPnews.com, March 31. http:// www.wtopnews.com/ (accessed July 9, 2007). Lowry, William R. 1992. Dimensions of federalism: State governments and pollution control policies. Durham, NC: Duke Univ. Press. Lutter, Randall, and Richard B. Belzer. 2000. EPA pats itself on the back. Regulation 23 (3): 23–38. Mazmanian, Daniel A., and Paul A. Sabatier. 1989. Implementation and public policy. With a new postscript. Lanham, MD: The Univ. Press of America. McCarthy, Jemes E., Claudia Copeland, Larry Parker, and Linda-Jo Schierow. 2007. Clean Air Act: A summary of the Act and its major requirements. Report No. RL30853. Washington, DC: Congressional Research Service. McFarlane, Deborah R. 1989. Testing the statutory coherence hypothesis: The implementation of federal family planning policy in the states. Administration and Society 20:395–422. McFarlane, Deborah R., and Marilyn M. Gruebel. 2006. Public management and policy implementation: Intersection, subset, or neither? Paper presented at the Fall Conference of the Association of Public Policy Analysis and Management, Madison, WI, November. Meier, Kenneth J., and Deborah R. McFarlane. 1995. Statutory coherence and policy implementation: The case of family planning. Journal of Public Policy 15:281–98. Meier, Kenneth J., and Laurence J. O’Toole. 2002. Public management and organizational performance: The effect of managerial quality. Journal of Policy Analysis and Management 21:629–43. Mintzberg, Henry. 1975. The manager’ job: Folklore and fact. Harvard Business Review 53:49–61. NACAA. 2009. Investing in clean air and public health. http://www.4cleanair.org/Documents/Reportneedssurvey042709.pdf (accessed April 6, 2010). Nicholson-Crotty, Sean, and Laurence J. O’Toole. 2004. Public management and organizational performance: The case of law enforcement agencies. Journal of Public Administration Research and Theory 14:1–18. O’Toole, Laurence J. 2000. Research on policy implementation: Assessment and prospects. Journal of Public Administration Research and Theory 10:263–88. ———. 2004. The theory-practice issue in policy implementation research. Public Administration 82:209–329. O’Toole, Laurence J., Kenneth J. Meier, and Sean Nicholson-Crotty. 2005. Managing upward, downward, and outward. Public Management Review 7:45–68. 23 24 Journal of Public Administration Research and Theory Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012 Pawson, Ray. 1989. A measure for measures: A manifesto for empirical sociology. New York, NY: Routledge. Portney, Paul R. 2000. An economic evaluation of the Clean Air Act. In Public policies for environmental protection, ed. Paul R. Portney and Robert N. Stavins. New York, NY: Resources for the Future. Rabe, Barry G. 2006. Power to the states: Promise and pitfalls of decentralization. In Environmental policy: New directions for the twenty-first century, 6th ed., ed. Norman J. Vig and Michael E. Kraft, 34–56. Washington, DC: CQ Press. ———. 2007. Racing to the top, bottom, or middle of the pack? In Environmental policy: New directions for the twenty-first century, 7th ed., ed. Norman J. Vig and Michael E. Kraft, 27–50. Washington, DC: CQ Press. Ringquist, Evan J. 1993. Environmental protection at the state level. New York, NY: M. E. Sharpe. Sabatier, Paul, and P. J. Klosterman. 1981. A comparative analysis of policy implementation under different statutory regimes. In Effective policy implementation, ed. Daniel Mazmanian and Paul Sabatier, 127–46. Lexington, MA: Lexington Books. Selden, Sally C., and Jessica E. Sowa. 2004. Testing a multi-dimensional model of organizational performance: Prospects and problems. Journal of Public Administration Research and Theory 14:395–416. Stern, David L. 1998. Progress on the environmental Kuznets curve? Environment and Development Economics 3:173–96. Sull, Donald N., and Charles Spinosa. 2007. Promised-based management: The essence of execution. Harvard Business Review, April. http://hbr.org/products/R0704E/R0704Ep4.pdf. Tsoukas, Haridimos. 1994. What is management? An outline of a metatheory. British Journal of Management 5:289–301. US Environmental Protection Agency (USEPA). 1997. The benefits and costs of the Clean Air Act, 1970 to 1990. http://www.epa.gov/air/sect812 (accessed July 29, 2008). ———. 1999. The benefits and costs of the Clean Air Act 1990 to 2010. ———. 2001. National air quality and emissions trend report, 2001. http://www.epa.gov/airtrends/ reports.html (accessed October 22, 2007). ———. 2007. The plain English guide to the Clean Air Act. http://www.epa.gov/air/oaq_caa.html/peg/ index.html (accessed October 22, 2007). Williams, Chuck. 2005. Management, 3rd ed. Mason, OH: Southwestern. Woods, Neal D., David M. Konisky, and Ann O’M Bowman. 2009. You get what you pay for: Environmental policy and public health. Publius: The Journal of Federalism 39:95–116. Zheng, Henry Yisheng. 2000. Exploring problem intractability in public policy implementation: The cases of superfund policy and low level radioactive waste management policy. Ph.D diss., The Ohio State Univ., 1999, Dissertation Abstracts International, 60/11, 4181.
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Capstone Project Topic

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Institution Affiliation
Course Name
Instructor
Date

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Capstone Project Topic-Annotated Bibliography

Tran, K. T., Nguyen, P. V., Dang, T. T., & Ton, T. N. (2018). The impacts of the highquality workplace relationships on job performance: a perspective on staff nurses in
Vietnam. Behavioral sciences, 8(12), 109. https://doi.org/10.3390/bs8120109
Staff relationship improvement is essential in any working place. Ohio State University
needs to improve its staff relationship to improve its performance in different areas like
technology. The article explains the importance of having good workplace relations. Working
relations among the staff are crucial for the overall performance rating at work and general
wellbeing. Great relationships among leaders and employees lead to great contributions to the
functioning of an organization. The author of this article explores some factors that influence the
performance of the staff. Interpersonal relationships at the workplace have been seen as essential
since they affect how the staff behaves. The relationship among staff affects the way information
gets received. To improve the staff relationships, the authors of the article states that the leaders
can play a great role in improving the relationships between the staff. The article is essential
because it shows adopting strategies like emotional support and respect are essential in
improving workplace relationships like in the Ohio State University. The article focuses on
nurses. The information on strategy can relate to Ohio. Communication and collaboration are
highly recommended strategies that improve the relationship between staff. Besides the author of
this article states that engaging each staff in the decision-making process. The strategies
mentioned in this article can be utilized in Ohio State University to ensure that staff relates well,
which will improve education and other development programs. Improved staff performance at

3
the University will improve the staff's productivity, which will help the University attain its goals
on technology, research, and knowledge transfer from one staff to another.

Joel Garfinkle. (n.d.). Building Positive Relationships at
Work. https://garfinkleexecutivecoaching.com/articles/build-positive-workrelationships/building-positive-relationships-at-work
The author of this article discusses the importance of good workplace interactions. The
strategies discussed by the author of this article can get utilized in Ohio State University to
improve its staff’s interaction which in turn will improve the performance of the University in
various major areas. Some of the strategies stated by the author of his article are crucial in
enhancing workplace relationships. The author notes that building positive workplace
relationships is vital since relationships can positively or negatively affect job satisfaction. With
great work relationships among the staff, they are a feeling of being comfortable. One strategy to
get used to each other is to speak positively of each person and share about oneself during
meetings. By letting people know about you more will improve the relationships. Another
important strategy that can get applied at Ohio State University is asking other staff members to
get involved in your activities and projects. The more the staff participates together in activities,
the more they improve their relationships. As noted in this article, another critical strategy of
enhancing relationships is initiating repeated communications and interactions. It helps the staff
know one another both professionally and personally, which improves the staff's performance.
Besides relationships can get improved through staff engaging in other activities that are not
related to work. This article is essential because it offers various strategies that can be adopted at
workplaces to ensure positive relationships among staff. The strategies are applicable in Ohio

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State University, and they will build positive interactions and improve the education and
performance of the staff. With good relationships, the staff will feel more comfortable and
satisfied in the working environment.
References
Joel Garfinkle. (n.d.). Building Positive Relationships at
Work. https://garfinkleexecutivecoaching.com/articles/build-positive-workrelationships/building-positive-relationships-at-work
Khoa T. Tran, Phuong V. Nguyen, Thao T.U. Dang, & Tran N.B. Ton. (2018). The Impacts of
the High-Quality Workplace Relationships on Job Performance: A Perspective on Staff
Nurses in Vietnam. https://doi.org/10.3390/bs8120109


Journal of Public Administration Research and Theory Advance Access published March 23, 2012

Desperately Seeking Management:
Understanding Management Quality and
Its Impact on Government Performance
Outcomes under the C l e a n A i r Act

Commented [WU1]: The main Topic of research and
Discussion
Commented [WU2]: The Author o the Article

Alexander C. Heckman
Franklin University

This study analyzes the impact of management quality, spending, problem severity, and
political factors on states’ air pollution control outcomes and provides insights for improving
the measures and methods used in public management and government performance
research. The analysis illustrates the importance of selecting proper outcome measures and
taking into account the interaction of management and spending when conducting
empirical analysis into the causes of government performance. Additionally, the author
demonstrates the benefits of conducting comparative empirical analysis using different, but
theoretically connected, outcome measures. The findings and analysis presented should be
of particular interest to public administration scholars seeking to conduct research that
produces practical insights for public managers and policy makers on improving public
management and government performance.The main Topic
THE CHALLENGE OF MEASURING MANAGEMENT

Public management studies consistently find that measures of management quality and the
use of certain management practices are positively related to government performance.
However, the results of these studies often do not provide useful, generalizable, guidance
about what practitioners should do to improve management practice. Unfortunately, management quality measures are frequently based on the subjective opinions of employees
within the organizations studied or they have been too narrowly defined for a particular
organizational or programmatic context to be of general applicability (Brudney, O’Toole,
and Rainey 2000; Donahue 2004; Meier and O’Toole 2002; Nicholson-Crotty and O’Toole
This article would not have been possible without the support and guidance of Trevor Brown at the Glenn School at
The Ohio State University. I also thank Anand Desai and the anonymous reviewers for their suggestions for
improving this study and Jenine Larrabee and Kyle Yaggi for their assistance in improving the quality of the
manuscript. Thanks also to R. Steven Brown and Mary Blakeslee of the Environmental Council of the States; Rachel
Weiss of the National Institute on Money in State Politics; Jim DeMocker and Tom McMullen of the USEPA; Neal
Johnson (now with Pearson Education) and the good people at the Pew Charitable Trust; and the helpful state and
local public servants in 47 states, for helping me to obtain and understand the data for this analysis. Address
correspondence to the author at alexander.heckman@franklin.edu.
doi:10.1093/jopart/mur068
ª The Author 2012. Published by Oxford University Press on behalf of the Journal of Public Administration Research
and Theory, Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012

ABSTRACT

Commented [WU3]: Provides a brief summary of what is
discussed in the article.

Commented [WU4]: The point summarizes the main
purpose of studying the above topic.

2

Journal of Public Administration Research and Theory

STUDY OVERVIEW

This study uses the GPP management measure to test management’s impact on environmental outcomes—a wholly different context than past studies using the GPP. The specific
questions addressed in the study are:
1) Does state management quality impact air pollution control outcomes?
2) What is the impact of management quality on air pollution control outcomes relative to other
state-level factors related to problem severity, resources, and the political environment?

The study incorporates design elements and data that make it well-suited for answering these questions. The important study elements include:
• Model Specification: The model specification was developed using the Mazmanian-Sabatier
implementation model (MSIM) illustrated in Figure 1, which is a well-established policy
implementation model.
• Outcome Measures: The analysis uses two different measures of performance outcomes
including a unique outcome measure that estimates reductions in air pollution emissions due
to national Clean Air Act (CAA). This second measure better reflects the outcomes sought by

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2004; O’Toole, Meier, and Nicholson-Crotty 2005; Selden and Sowa 2004). Additionally,
management measures used in the literature are often opaque as to what constitutes good
management. For instance, Meier and O’Toole (2002) used the residual from a regression
model of a superintendent’s salary as a measure of managerial quality and found that good
management had a positive impact on student learning outcomes. Although findings from
such studies may support the notion that good management produces good performance,
they shed little light on general steps for improving public management practice and policy
implementation outcomes.
The lack of concrete, yet general, measures of management quality represents a major
obstacle to producing pragmatic insights about the public management-government
performance relationship (Boyne 2003, 2004; Boyne et al. 2005). Although Meier and
O’Toole (2002) have stated that this measurement challenge is ‘‘intractable,’’ developing
more useful, general measures of management quality is essential if public administration
research is to produce practical knowledge for improving public management practice that
results in better government performance.
A significant exception to the lack of general and concrete measures of management
quality is the management grades assigned to the 50 states in 1999, 2001, 2005, and 2008
by the Government Performance Project (GPP), which is currently managed by the Pew
Center on the States. The GPP management capacity measure provides detailed, general,
criteria that clearly define good management practice. The GPP grades represent the best,
criteria-based, multidimensional measure that is regularly applied to a large number of
governments in the United States (Borins 2005; Ingraham, Joyce, and Kneedler 2003).
Studies using the GPP suggest that it is a promising way to operationalize the concept
of management quality in a general way that provides practical insights into what constitutes good management practice (Burke and Wright 2002; Coggburn and Schneider 2003;
Donahue, Selden, and Ingraham 2000; Knack 2002).

Commented [WU5]: The point is important to because it
provides the major challenges faced in measuring
management.

Commented [WU6]: Research Questions to guide in the
research

Heckman Management Quality and Its Impact on Government Performance

3

Figure 1
Mazmanian and Sabatier Implementation Success Model

• Causal Measures and Data: The analysis also uses measures of management quality and
interest group influence that more accurately capture these concepts than similar studies (e.g.,
Lester, Franke, and Bowman 1983). Also, the study includes better data on the total amounts
spent within each state on air pollution control efforts. The data were collected by the author
and provide the most accurate estimates available of these expenditures.
• Comparative, Large-N Analysis: Two different measures of air pollution control outcomes
affected by the same causal variables are modeled, which enables a comparative analysis of
the empirical results. Also, air pollution outcomes for 47 states are modeled, providing
generalizable results not found in many studies examining government performance,
particularly studies on policy implementation.

Together, these elements create a unique study that sheds new light on the
management-performance connection and the causal factors affecting national air pollution
control outcomes.
CONTEXT FOR ASSESSING MANAGEMENT IMPACT

National air pollution policy provides a useful context for assessing the impact of state
management quality on performance outcomes because it provides a common policy
design in regards to air pollution control, but state-level implementation efforts and characteristics are critical determinants of the extent to which policy goals are achieved
(Woods, Konisky, and Bowman 2009). The CAA is the primary air pollution control
legislation in the United States.
Under the CAA, the US Environmental Protection Agency (USEPA) sets national
ambient air quality standards to ensure basic protection of human health and natural resources, but state and local governments are primarily responsible for enforcement of the

Downloaded from http://jpart.oxfordjournals.org/ at Franklin University on April 5, 2012

policy makers and achieved by policy implementers, than similar studies using only aggregate
emission outcome measures (e.g., Carson, Jeon, and McCubbin 1997; Lowry 1992).

Commented [WU7]: The sub-topic is important because
it provides important context of assessing the impact of
state management quality on performance outcomes.

4

Journal of Public Administration Research and Theory

THEORETICAL MODEL AND MANAGEMENT QUALITY MEASURE

The MSIM is one of the most comprehensive and empirically tested policy implementation
theories and was developed to model intergovernmental implementation situations like the
one examined in this study—see Figure 1 (McFarlane and Gruebel 2006; Zheng 2000).
The MSIM states that government performance is the result of three categories of
factors (Mazmanian and Sabatier 1989):
Statutory: The statutory structure of a policy is set in law by elected officials to direct and
constrain policy implementation. According to the MSIM, policy implementation should be
more successful when goals are clearly understood, there is a sound understanding of the causes
of the problem, and sufficient resources are provided to achieve policy goals. Under the CAA,
the policy design and goals are set by the national government and is the same for all states. Total
spending on implementing air pollution control policies is the main statutory variation across the
states. The combined decisions of national, state, and certain local governments determine the
level of resources spent on air pollution control efforts within each state.
Nonstatutory: Nonstatutory factors are not in direct control of national policy makers but impact
the policy outcomes achieved by officials implementing the policy. Relevant nonstatutory
factors include the support or opposition of the general public and influential interest groups for
the policy and the skill of implementing officials or management quality within each state.

1

Appendix 1 summarizes the changes made to the CAA in 1990 that are most relevant to this analysis.

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policy. All 50 states have been delegated responsibility for implementing the CAA provisions and states face financial and other sanctions from the USEPA if they fail to adequately carry out their duties (ECOS 2007; USEPA 2007). States and certain local
environmental agencies implement the CAA by monitoring air quality, inspecting facilities
and enforcing air pollution regulations. Amendments to the CAA enacted in 1990 further
increased the regulatory role states play and strengthened the ability of the states to meet
national air pollution standards (Rabe 2006).1
Evidence of the prominent role states play in carrying the CAA can be seen in USEPA
statistics. Nearly all the air pollution data in the USEPA’s databases are collected and
reported by the states (Brown and Green 2001; ECOS and USEPA 1999). States also bear
most of the financial responsibility for enforcing air pollution control programs. On average, more than $1 billion per year is spent on air pollution control activities within each of
the 47 states included in this study. However, ac...


Anonymous
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