![Sample our Politics & International Relations journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5947/TOC-Subject-Sample-2021-Politics-International-Relations.jpg"})
ABSTRACT
Some scholars equate fiscal slack with organizational inefficiency, while others argue that it is a useful environmental buffer. This study takes the first step in reconciling these opposing views, by classifying fiscal slack as absorbed and unabsorbed slack in public organizations. In a sample of 1,000 Texas public school districts over 17 years, fund balance (unabsorbed fiscal slack) does not seem to affect student performance, unless there is a major downward budget shock. In the absence of a negative budget shock, non-instructional spending per pupil (absorbed fiscal slack) has a negative impact on performance change in an average school district, but no meaningful impact on student performance during a major budget shock.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. Public choice scholars focus on organizational efficiency (see Niskanen Citation1971). Management scholars, notably Cyert and March (Citation1963), focus on organizational stability and effectiveness. These differences in focus lead to contradictory expectations about slack as a buffer.
2. See Walsh (Citation2011, Citation2012) for a discussion on ‘lazy bureaucrats’.
3. Legislative Budget Board Fiscal Size Up 2012–2013 Biennium.
5. The same concerns and strategies were revealed during personal conversations with several of these school district business managers.
6. Marlowe (Citation2011) does not categorize slack as absorbed or unabsorbed but uses unreserved general fund balance, total general fund balance, and unrestricted net assets as three slack measures. We would categorize all three as unabsorbed slack measures.
7. Texas has a large and growing contingent of charter schools, which are not included in this analysis. We also exclude districts that were only operational during part of the analysis period and districts that lack reliable data for one or more key indicators.
8. The data come from TEA’s snapshot (http://ritter.tea.state.tx.us/perfreport/snapshot/) and PEIMS (http://tea.texas.gov/financialstandardreports/).
9. Source: Texas Education Agency.
10. Source: Texas Education Agency.
11. Negative budget shocks hurt extremely poor district more than extremely rich districts. By excluding a few extremely rich school districts, that have over 85 per cent fund balance surplus, we lose fewer than 300 observations.
12. Despite their best efforts, Texas school districts could not entirely protect student performance from the detrimental effect of the 2011 funding shock. This was primarily because of a high volume of teacher attrition, which constituted 85 per cent of staffing losses from 2010–2011 to 2012–2013 school years that lead to larger classroom sizes leading to ‘teacher fatigue,’ and adversely impacted student performance (Goff and Sanborn Citation2012). Research suggests that besides remuneration, work environment plays a key role in influencing teacher attrition rates (Gritz and Theobald Citation1996; Falch and Strøm Citation2005). And, the cutbacks that were made directly and indirectly impacted the work environment in schools.
13. In school districts, a hierarchical administrative system controls the flow of resources and coordinates key activities (Brewer Citation1996). The administrative cadre in a typical district comprises of superintendents, at the district level, and their assistants and at the school level, this includes principals, assistant principals, departmental heads, professional/‘paraprofessional’ support staff, and ‘nonprofessional’ staff. Examples of paraprofessional staff would be psychologists, and teaching aides, and nonprofessional staff includes secretarial, transportation, and building maintenance workers (112).
14. Excluding food service expenditures also removes the potentially confounding correlation between student socio-economic status (which is measured by student participation in the National School Lunch Program) and non-instructional expenditures per pupil.
15. An analogous technique was used by Rattso (Citation1999) to study shocks to the Norwegian national economy.
16. For sensitivity analysis shocks at 5, 15, and 18 per cent thresholds were also considered and their outcomes are reported at the end of the findings section.
17. We express the variables in this way to simplify interpretation.
18. The F-statistic for the hypothesis that the two coefficients are equal is 3.55 with one and 1,037 degrees of freedom. The probability of a greater F-statistic is 0.0597.
19. Bootstrapping the standard errors yields nearly identical results. The bootstrapped versions of – are available upon request.
Additional information
Notes on contributors
Abhisekh Ghosh Moulick
Abhisekh Ghosh Moulick is an Assistant Professor in the Department of Political Science at the University of Oklahoma, where he is affiliated with the nonprofit and public administration concentrations at the graduate and undergraduate levels. Dr. Ghosh Moulick conducts research in financial management in various organizational and industry settings.
Lori L. Taylor
Lori L. Taylor is the Director of the Mosbacher Institute for Trade, Economics and Public Policy at Texas A&M University, and the Verlin and Howard Kruse ’52 Founders Associate Professor in the Bush School of Government and Public Service. Dr. Taylor has written extensively on variations in the cost of education and the determinants of school district efficiency.