Utilization of Employment Tax Credits: An Analysis of the Empowerment Zone Wage Tax Credit

This paper provides estimates of utilization for the Empowerment Zone (EZ) wage tax credit, a subsidy claimed by employers who operate in and hire residents of federally designated areas experiencing economic distress. The EZ credit is currently the largest employer‐based wage tax credit in the federal tax code in terms of dollars claimed, with almost $250 million claimed in 2002. I show that about 6.4 percent (and at least 3.5 percent) of the working age population was claimed under the EZ wage credit in 1999. In addition, I estimate that 24.2 percent (and at least 13.1 percent) of those employed inside of the target area were claimed for the credit. I create these national estimates of use with information on credit dollars claimed from the Internal Revenue Service and population data on the eligible population from the census. These measures of tax credit use are an alternative to the use rate of firms that are presented in the existing literature, and reveal how effective the credit is at reaching residents of the target area.     

Credit Reform, Negative Subsidies, and FHA

After several years' experience with the new budgetary treatment of federal credit activity, or credit reform, it is appropriate to consider how this innovation is working. One objective of the new approach was to provide both estimates of the cost of credit assistance and a means of monitoring the performance of those estimates over time. In at least one—admittedly difficult—case, FHA single-family mortgage insurance, the reform is not succeeding in reporting the performance of the subsidy estimate because the agency's budget submissions are not consistent with the new accounting. This failure may result from the agency's inability to accept or adopt the fundamental changes in accounting concepts affected by credit reform. This article attempts to explain some of those changes and to show how they may be used to provide relevant information in the budget.     

The Impact of Budget Stabilization Funds on State General Obligation Bond Ratings

This study examines the impact of budget stabilization funds (BSFs) on state general obligation (GO) bond credit ratings. While a number of past empirical papers have examined the effect of various fiscal institutions on state GO bond ratings; to date, BSFs have been largely ignored in the literature. Model estimates show that neither the choice to have a statutory BSF versus a constitutional BSF or the size of a BSF has any apparent impact on credit ratings. However, weak deposit rules are associated with lower credit ratings while weak withdrawal rules are associated with higher credit ratings.     

Credit scores,race, and residential sorting

Credit scores have a profound impact on home purchasing power and mortgage pricing, yet little is known about how credit scores influence households' residential location decisions. This study estimates the effects of credit scores on residential sorting behavior using a novel mortgage industry data set combining household demographic, credit, and financial data with property location information and detailed community attribute data. I employ the data set to estimate a discrete‐choice residential sorting model. I find that credit scores significantly predict residential sorting behavior and models that do not account for credit score provide biased estimates of housing utilities for black households in particular. Simulation results show that increases in credit score are associated with increases in the consumption of higher‐priced homes in more expensive school districts, higher‐quality public schools, and proximity to urban/metropolitan areas. © 2010 by the Association for Public Policy Analysis and Management.     

Extending the EITC to noncustodial parents: Potential impacts and design considerations

This paper examines the noncustodial parent earned income tax credit (NCP EITC), a new type of credit recently enacted in New York and Washington, D.C., and proposed by Senator Bayh and then‐Senator Obama in 2007. The NCP EITC offers an earned income tax credit to low‐income noncustodial parents who work and pay their full child support. This paper provides background information about the policy and presents national estimates of eligibility and benefits for an NCP EITC under three alternative policy scenarios. It also discusses several key design and implementation issues. © 2010 by the Association for Public Policy Analysis and Management.     

A note on sampling variance estimates for Social Security program participants from the Survey of Income and Program Participation

The Census Bureau's Survey of Income and Program Participation (SIPP) provides data that can be used to study the characteristics of Old-Age, Survivors, and Disability Insurance (OASDI) and Supplemental Security Income (SSI) program participants. It is important that estimates of sampling errors accompany such studies because the estimates may have large sampling errors due to the small number of sample cases available for specific analyses. The generalized sampling variances provided by the Census Bureau did not identify separately either program's participants and, therefore, do not pertain directly to analyses of these groups. This article describes an approach to the direct computation of sampling variances for OASDI and SSI program participants. The approach uses the pseudo stratum and half-sample codes available in SIPP public use data files. A table of generalized standard errors is constructed for participants of both programs aged 18 or older. Generalized standard errors could not be computed for child beneficiaries under age 18 because of a wide variation of design effects across subpopulation estimates.     

On the accuracy of regulatory cost estimates

This study compares ex ante estimates of the direct costs of individual regulations to ex post assessments of the same regulations. For total costs the results support conventional wisdom, namely that the costs of regulations tend to be overestimated. This is true for 14 of the 28 rules in the data set discussed, while for only 3 rules were the ex ante estimates too low. For unit costs, however, the story is quite different. At least for EPA and OSHA rules, unit cost estimates are often accurate, and even when they are not, overestimation of abatement costs occurs about as often as underestimation. In contrast, for those rules that use economic incentives, unit costs are consistently overestimated. The difference between the total‐cost and the unit‐cost results is caused by frequent errors in estimates of the effects of individual rules, which suggests, in turn, that the rule's benefits may also be overestimated. The quantity errors are driven both by difficulties in determining the baseline and by incomplete compliance. In cases of unit‐cost overestimation, unanticipated technological innovation appears to be an important factor — especially for economic incentive rules, although procedural and methodological explanations may also apply. © 2000 by the Association for Public Policy and Management.     

Getting it (approximately) right (and center and left!): Reliability and uncertainty estimates for the comparative manifesto data

The extensive estimates of party policy preferences produced by the CMP (Comparative Manifesto Project, now MARPOR) have proved robust and valid over a wide variety of research applications. But all estimates carry some error. We demonstrate that one of the two existing assessments of non-systematic error in the CMP data strongly overstates their reliability while the other understates it, leaving much potential for mis-estimation. We develop a new method which extends classical test theory and directly estimates overall data reliability; reliabilities and standard errors of measurement for each party system; and standard errors of measurement for each data-point. These should facilitate use of the CMP policy scores which are usually the only ones available for extended party and policy research.     

Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects

e-mail: tpluem{at}essex.ac.uk (corresponding author) This paper suggests a three-stage procedure for the estimationof time-invariant and rarely changing variables in panel datamodels with unit effects. The first stage of the proposed estimatorruns a fixed-effects model to obtain the unit effects, the secondstage breaks down the unit effects into a part explained bythe time-invariant and/or rarely changing variables and an errorterm, and the third stage reestimates the first stage by pooledOLS (with or without autocorrelation correction and with orwithout panel-corrected SEs) including the time-invariant variablesplus the error term of stage 2, which then accounts for theunexplained part of the unit effects. We use Monte Carlo simulationsto compare the finite sample properties of our estimator tothe finite sample properties of competing estimators. In doingso, we demonstrate that our proposed technique provides themost reliable estimates under a wide variety of specificationscommon to real world data. Authors' note: Earlier versions of this paper have been presentedat the 21st Polmeth Conference at Stanford University, PaloAlto, July 29–31, 2004, the 2005 MPSA Conference in Chicago,April 7–10, and the APSA Annual Conference 2005 in Washington,September 1–4 2005. We thank the referees of PoliticalAnalysis and Neal Beck, Greg Wawro, Donald Green, Jay Goodliffe,Rodrigo Alfaro, Rob Franzese, Jörg Breitung, and PatrickBrandt for helpful comments on previous drafts. Any remainingdeficiencies are our responsibility.     

Much Ado about Nothing? The Size and Credit Quality Implications of Municipal Other Postemployment Benefit Liabilities

This paper presents estimates of the size and scope of other postemployment benefit (OPEB) liabilities among municipal governments. The findings indicate these liabilities vary substantially, ranging from less than a dollar per capita to more than $2,000 per capita. Those liabilities were then incorporated into separate models of credit ratings and borrowing costs. Results suggest OPEB liabilities do not directly affect credit quality, but the interaction between an issuer's fiscal capacity to address its liability does have a notable effect.     

政府控制、制度环境与信贷资源配置

将政府控制内部结构与制度环境纳入统一分析框架,深入研究了政府控制内部结构对银行信贷资源配置的影响,以及在不同制度环境下政府控制内部结构对信贷资源配置发挥的作用是否有所不同。研究表明:政府行政级别越低,越有动机干预银行信贷资源配置,帮助其所控制公司获得银行贷款,公司银行借款水平就越高。与通过实业主体控制的公司相比,在政府通过国有资产管理机构控制的上市公司,政府通过干预银行信贷资源配置帮助公司获取银行贷款的行为更为便利,该类公司具有较高的银行借款水平。与制度环境较差的地区相比,在制度环境较好的地区,政府控制内部结构对银行信贷资源配置发挥的作用相对较小。研究有助于深入理解信贷资源配置行为的制度根源。     

STRENGTHENING THE REGRESSION DISCONTINUITY DESIGN USING ADDITIONAL DESIGN ELEMENTS: A WITHIN‐STUDY COMPARISON

The sharp regression discontinuity design (RDD) has three key weaknesses compared to the randomized clinical trial (RCT). It has lower statistical power, it is more dependent on statistical modeling assumptions, and its treatment effect estimates are limited to the narrow subpopulation of cases immediately around the cutoff, which is rarely of direct scientific or policy interest. This paper examines how adding an untreated comparison to the basic RDD structure can mitigate these three problems. In the example we present, pretest observations on the posttest outcome measure are used to form a comparison RDD function. To assess its performance as a supplement to the basic RDD, we designed a within‐study comparison that compares causal estimates and their standard errors for (1) the basic posttest‐only RDD, (2) a pretest‐supplemented RDD, and (3) an RCT chosen to serve as the causal benchmark. The two RDD designs are constructed from the RCT, and all analyses are replicated with three different assignment cutoffs in three American states. The results show that adding the pretest makes functional form assumptions more transparent. It also produces causal estimates that are more precise than in the posttest‐only RDD, but that are nonetheless larger than in the RCT. Neither RDD version shows much bias at the cutoff, and the pretest‐supplemented RDD produces causal effects in the region beyond the cutoff that are very similar to the RCT estimates for that same region. Thus, the pretest‐supplemented RDD improves on the standard RDD in multiple ways that bring causal estimates and their standard errors closer to those of an RCT, not just at the cutoff, but also away from it.     

Using Ecological Inference Point Estimates as Dependent Variables in Second-Stage Linear Regressions

The practice of using point estimates produced by the King ecologicalinference technique as dependent variables in second-stage linearregressions leads to second-stage results that, in general,are inconsistent. This conclusion holds even when all assumptionsbehind King's ecological technique are satisfied. Second-stageinconsistency is a consequence of the fact that King-based pointestimates of disaggregated quantities contain errors correlatedwith the true quantities the estimates measure. Our findingson second-stage inconsistency, as well as a fix that we propose,follow from econometric theory in conjunction with an analysisof simulated and real ecological data sets.     

Formulating disaster relief when needs are unknown.

As in most cases of natural disasters, relief needs arising out of the Mount St. Helens volcanic eruptions in May 1980 were greatly overestimated. Technical, bureaucratic, and political considerations all contribute to the upward bias in such cases. The errors in early estimates of relief needs can be reduced by systematic means. But more important than obtaining good early estimates is maintaining an effective control over actual disaster relief expenditures. As it turns out, the more effective systems of control usually go hand in hand with poorer early estimates, creating a dilemma for the management for disaster relief.     

Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap

Keith T. Poole Center for Advanced Study in the Behavioral Sciences and Department of Political Science, University of Houston, Houston, TX 77204-3011 e-mail: kpoole{at}uh.edu Over the last 15 years a large amount of scholarship in legislativepolitics has used NOMINATE or other similar methods to constructmeasures of legislators' ideological locations. These measuresare then used in subsequent analyses. Recent work in politicalmethodology has focused on the pitfalls of using such estimatesas variables in subsequent analysis without explicitly accountingfor their uncertainty and possible bias ( Herron and Shotts2003, Political Analysis 11:44–64). This presents a problemfor those employing NOMINATE scores because estimates of theirunconditional sampling uncertainty or bias have until now beenunavailable. In this paper, we present a method of forming unconditionalstandard error estimates and bias estimates for NOMINATE scoresusing the parametric bootstrap. Standard errors are estimatedfor the 90th U.S. Senate in two dimensions. Standard errorsof first–dimension placements are in the 0.03 to 0.08range. The results are compared with those obtained using theMarkov chain Monte Carlo estimator of Clinton et al. (2002,Stanford University Working Paper). We also show how the bootstrapcan be used to construct standard errors and confidence intervalsfor auxiliary quantities of interest such as ranks and the locationof the median senator.     

Estimating Regression Models in Which the Dependent Variable Is Based on Estimates

e-mail: jblewis{at}ucla.edu (corresponding author) e-mail: dlinzer{at}ucla.edu Researchers often use as dependent variables quantities estimatedfrom auxiliary data sets. Estimated dependent variable (EDV)models arise, for example, in studies where counties or statesare the units of analysis and the dependent variable is an estimatedmean, proportion, or regression coefficient. Scholars fittingEDV models have generally recognized that variation in the samplingvariance of the observations on the dependent variable willinduce heteroscedasticity. We show that the most common approachto this problem, weighted least squares, will usually lead toinefficient estimates and underestimated standard errors. Inmany cases, OLS with White's or Efron heteroscedastic consistentstandard errors yields better results. We also suggest two simplealternative FGLS approaches that are more efficient and yieldconsistent standard error estimates. Finally, we apply the variousalternative estimators to a replication of Cohen's (2004) cross-nationalstudy of presidential approval.     

Federal Credit Reform

The Congress has now enacted, and the president has signed, legislation requiring credit reform accounting in the 1992 budget. This article summarizes the state of federal budgeting for credit activities, covering (1) where we are now with regard to budgeting for ciedit, (2) how we got where we are, (3) the major weaknesses of the older approaches and why credit reform is important, and (4) the fundamental elements of the recently enacted credit reform legislation.     

Accruing Retirement Costs for Federal Employees

The president's 2003 budget proposed that federal agencies pay the full cost of their employees' pension and retiree health benefits as such benefits are earned starting in 2003. The main reason for the proposed change is to provide policymakers and agency managers with a more complete measure of the cost of providing current services. The main disadvantage of the proposal is that estimates of the accrual costs of retiree health benefits are subject to large errors. The proposed change would not increase total outlays, nor would it affect the budget deficit or surplus.     

投融资平台公司信用风险与地方政府信用失序——以法律为视角

法律冲突与制度扭曲环境下的投融资平台公司,从诞生之日起即具有结构性信用风险,而平台公司的信用风险与地方政府的信用具有相关性,其所具有的传导效应构成地方政府信用风险、宏观经济结构调整风险、土地政策调整风险、银行系统风险、财政风险这样一条具有多米诺骨牌效应的信用风险链并或将成为推手。加强地方政府的信用治理,从财政体制上、法律制度上规范地方政府信用秩序是防范平台公司信用风险的根本手段。     

Real Denial Rates: A New Tool to Look at Who Is Receiving Mortgage Credit

ABSTRACT

The observed mortgage denial rate (ODR), calculated from Home Mortgage Disclosure Act (HMDA) data, is often used to measure mortgage credit availability, but it does not account for shifts in applicants’ credit profiles. In this article, we develop an additional tool, which we call the real denial rate (RDR), as a way to account for credit differences and hence more consistently measure denial rates and mortgage credit accessibility. We match HMDA data with CoreLogic proprietary data to obtain both borrower demographic information (e.g., income and race and ethnicity) and mortgage credit characteristics (e.g., loan-to-value ratios, debt-to-income ratios, and credit scores). We account for shifts in applicants’ credit profiles by considering only the denial rate of low-credit-profile applicants. Our RDR results show that conventional mortgages have higher denial rates than government mortgages do, racial and ethnic differences are smaller than the ODR indicates but are not eliminated, and small-dollar mortgages have higher RDRs, particularly in the government loan channel.