ON THE SOURCES OF HETEROGENEITY IN BANKING EFFICIENCY LITERATURE

This study reviews the empirical literature on banking efficiency by conducting a meta‐regression analysis. The meta‐dataset consists of 1661 observations retrieved from 120 papers published over the period 2000–2014. While the role of study design and method‐specific characteristics of primary studies is evaluated, the focus concerns regulation in banking. The results are fourfold. First, parametric methods always yield lower levels of banking efficiency than non‐parametric studies. Second, banking efficiency is higher in studies using the value‐added approach rather than the intermediation method. Third, efficiency scores also depend on the journal's ranking and on the number of observations and variables used in the primary papers. Finally, regulation matters: primary papers focusing on countries with a liberalized banking industry provide higher values for efficiency scores.     

WHICH FISCAL MULTIPLIERS ARE REGIME‐DEPENDENT? A META‐REGRESSION ANALYSIS

We analyse whether estimated multiplier effects are systematically higher if the economy suffers a downturn. For that purpose, we conduct a meta‐regression analysis on a unique data set of 98 empirical studies with more than 1800 observations on multiplier effects and control for regime‐dependence of the multiplier. We find that spending multipliers are much higher (by about 0.7–0.9 units) during a downturn. Tax multipliers are not sensitive to the economic regime, and generally lower than spending multipliers. Finally, for all spending categories other than government consumption, the multiplier significantly exceeds one during downturns.     

FDI AND TAXATION: A META‐STUDY

Abstract In this paper we extend former meta‐analyses on FDI and taxation in three ways. First, we add 16 recent publications. Second, we code additional meta‐regressor variables addressing important issues in research on FDI and taxation. Third, we refer to the sophisticated meta‐analytical methodology and present a coherent strategy to choose the meta‐regression estimator most suitable for the meta‐data at hand. As compared to prior surveys, the meta‐analysis is thus based on a much broader methodological basis and a considerably richer meta‐data set. The median tax semi‐elasticity of FDI based on 704 primary estimates is 2.49 in absolute terms. The precision weighted average of the full sample of semi‐elasticities is 2.55, again in absolute terms. Moreover, our meta‐analysis shows that there is a publication bias in the primary literature. Meta‐regressions show that studies based on aggregate data report systematically larger semi‐elasticities than firm‐level analyses, that integrating bilateral tax regulations into effective tax rates leads to more effective measurement of adverse tax incentives on foreign investment, and that tax effects are not compensated by public spending.     

The operating efficiency of financial holding and nonfinancial holding banks—Epsilou‐based measure metafrontier data envelopment analysis model

Previous bank efficiency studies assumed that the same efficient frontier system exists in different types of banks, but the conventional radial data envelopment analysis (DEA) model slacks are not counted in efficiency scores, and nonradial DEA models do not consider radial features. This paper develops an Epsilou‐based measure meta‐DEA approach for measuring the efficiencies and technology gaps of different bank types. The results are as the follows: The average efficiency and technology gaps of nonfinancial holding banks are better than those of financial holding banks. The nonfinancial holding banks are more efficient than financial holding banks in investment and other income.     

WHAT'S TO KNOW? PUZZLES IN THE LITERATURE ON THE VALUE OF STATISTICAL LIFE

Abstract Notwithstanding the general acceptance of the value of statistical life (VSL) estimates for policy assessment purposes, several important unresolved issues remain. First, the results from revealed preference studies are systematically higher than those from stated preference studies, potentially limiting the usefulness of stated preference studies in generalizing the VSL estimates to different populations and kinds of risks. Second, extrapolating the results of meta‐analyses to project the VSL for different population groups requires that such generalization be reflective of the underlying economic content of what average VSL estimates reflect. Third, government agencies within and across countries place differing emphasis on types of VSL studies as well as differing reliance on individual studies versus meta‐analyses. Usually, there is no justification provided for the chosen approach.     

Meta‐Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection*

This study investigates the small‐sample performance of meta‐regression methods for detecting and estimating genuine empirical effects in research literatures tainted by publication selection. Publication selection exists when editors, reviewers or researchers have a preference for statistically significant results. Meta‐regression methods are found to be robust against publication selection. Even if a literature is dominated by large and unknown misspecification biases, precision‐effect testing and joint precision‐effect and meta‐significance testing can provide viable strategies for detecting genuine empirical effects. Publication biases are greatly reduced by combining two biased estimates, the estimated meta‐regression coefficient on precision (1/Se) and the unadjusted‐average effect.     

Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations

Analyzing the effect of local government decision‐making competition on regional carbon emissions is important for reducing carbon emissions in rapidly urbanizing areas. Taking the energy rebound effect into account, this study analyzes the effect on carbon emissions of competition between local governments in decision making. Focusing on China's three urban agglomerations, this study further discusses how to avoid this influence. The results show that local government decision‐making competition is one of the main causes of the regional “green paradox”; the effect of local government decision‐making competition on carbon emissions has significant regional heterogeneity and spatial dependence, and the short‐term energy rebound effect is greater than the long‐term energy rebound effect; and local government decision‐making competition has three effects on carbon emissions that also have interaction and substitution effects between them: factor market distortion, investment bias, and the “race to the bottom” of environmental policies. However, four measures can reduce the effect of local government decision‐making competition on carbon emissions: one, improving the performance evaluation system of local governments; two, promoting the marketization of factor prices; three, improving both the energy efficiency and upgrading of industrial structures; and four, introducing macro emission reduction policies that allow the central government to intervene directly.     

CORRUPTION'S DIRECT EFFECTS ON PER‐CAPITA INCOME GROWTH: A META‐ANALYSIS

Corruption is a symptom of weak institutional quality and could have potentially adverse effects on economic growth. However, heterogeneity in reported findings makes it difficult to synthesize the evidence base with a view to test competing hypotheses and/or support evidence‐based policy and practice. To address this issue, we have extracted 327 estimates of corruption's direct effect on per‐capita GDP growth from 29 primary studies, following a peer‐reviewed and pre‐published systematic review protocol. Precision‐effect and funnel asymmetry tests indicate that corruption has a negative effect on per‐capita GDP growth after controlling for publication selection bias and within‐study dependence. However, multivariate meta‐regression analysis results indicate that the overall effect is not robust to inclusion of moderating variables through a general‐to‐specific procedure for model specification. We report that the marginal effect of corruption on per‐capita GDP growth is more adverse when the primary study estimates relate to long‐run growth, are based on low‐income‐country data only, and extracted from journal papers. The effect is less adverse in studies that use the International Country Risk Guide corruption perceptions index and in those reporting estimates from two‐stage least‐squares estimations.     

New Evidence on Class Size Effects: A Pupil Fixed Effects Approach*

The impact of class size on student achievement remains a thorny question for educational decision makers. Meta‐analyses of empirical studies emphasize the absence of class‐size effects but detractors have argued against such pessimistic conclusions because many of the underlying studies have not paid attention to the endogeneity of class size. This article uses a stringent method to address the endogeneity problem using Trends in International Mathematics and Science Study data on 47 countries. We measure the class size effect by relating the difference in a student's achievement across subjects to the difference in his/her class size across subjects. This (subject‐differenced) within‐pupil achievement production function avoids the problem of the non‐random matching of children to specific schools, and to classes within schools. The results show a statistically significant negative effect of class size in 14 countries, but the effect size is small in most cases. Several robustness tests are carried out, including control for students’ subject‐specific ability and subject‐specific teacher characteristics, and correction for possible measurement error. Thus, our approach to addressing the endogeneity problem confirms the findings of meta‐analyses that find little support for class size effects. Additionally, we find that class size effects are smaller in countries with higher teacher quality.     

WHAT HAVE WE LEARNED FROM THREE DECADES OF RESEARCH ON THE PRODUCTIVITY OF PUBLIC CAPITAL?

The last three decades have witnessed a great deal of research effort devoted to measuring the private output elasticity of public capital. The wide range of available estimates have precluded any consensus so far, however. This paper reconciles the empirical findings of the literature by quantitatively analyzing a sample of 578 estimates collected from 68 studies for the 1983–2008 period. Using meta‐regression analysis, we show how study design characteristics and publication bias can explain a large fraction of the variation across estimates. We find a short‐run output elasticity of public capital supplied at the central government level of 0.083, which increases to 0.122 in the long run. If, in addition, only core infrastructure at a regional/local level of government is considered, these estimates are almost doubled. The average output elasticity of public capital amounts to 0.106. Our results suggest that public capital is undersupplied in OECD economies.     

Random Effects Misspecification Can Have Severe Consequences for Random Effects Inference in Linear Mixed Models

There has been considerable and controversial research over the past two decades into how successfully random effects misspecification in mixed models (i.e. assuming normality for the random effects when the true distribution is non‐normal) can be diagnosed and what its impacts are on estimation and inference. However, much of this research has focused on fixed effects inference in generalised linear mixed models. In this article, motivated by the increasing number of applications of mixed models where interest is on the variance components, we study the effects of random effects misspecification on random effects inference in linear mixed models, for which there is considerably less literature. Our findings are surprising and contrary to general belief: for point estimation, maximum likelihood estimation of the variance components under misspecification is consistent, although in finite samples, both the bias and mean squared error can be substantial. For inference, we show through theory and simulation that under misspecification, standard likelihood ratio tests of truly non‐zero variance components can suffer from severely inflated type I errors, and confidence intervals for the variance components can exhibit considerable under coverage. Furthermore, neither of these problems vanish asymptotically with increasing the number of clusters or cluster size. These results have major implications for random effects inference, especially if the true random effects distribution is heavier tailed than the normal. Fortunately, simple graphical and goodness‐of‐fit measures of the random effects predictions appear to have reasonable power at detecting misspecification. We apply linear mixed models to a survey of more than 4 000 high school students within 100 schools and analyse how mathematics achievement scores vary with student attributes and across different schools. The application demonstrates the sensitivity of mixed model inference to the true but unknown random effects distribution.     

THE EURO'S TRADE EFFECT: A META‐ANALYSIS

Many studies have estimated the trade effect of the euro, but their results vary greatly. This meta‐analysis collects 3323 estimates of the euro effect along with 28 characteristics of estimation design from almost 60 studies and quantitatively examines the literature. The results show evidence of publication bias, but they also suggest that the bias decreases over time. After correcting for the bias, the meta‐analysis shows that the literature is consistent with an effect ranging between 2% and 6%. The results from Bayesian model averaging, which takes into account model uncertainty, show that the differences among estimates are systematically driven by data sources, data structure, control variables, and estimation techniques. The mean reported estimate of the euro's trade effect conditional on best‐practice approach is 3%, but is not statistically different from zero.     

RISE OF THE FIDUCIARY STATE: A SURVEY OF SOVEREIGN WEALTH FUND RESEARCH

We survey the literature documenting the rise of sovereign wealth funds (SWFs), which, with assets under management of over $5.4 trillion at year‐end 2014, are a major force in global finance. Research papers have analyzed the evolution of SWFs from stabilization funds to stand‐alone wealth management funds; we both survey this research and show that more than 25 countries have launched or proposed new SWFs since January 2008. The most salient and controversial feature of SWFs is that they are state‐owned; we survey the existing literature on state ownership and discuss what this predicts about the efficiency and beneficence of government control of SWF assets. We discuss the documented importance of SWF funding sources (oil sales revenues versus excess reserves from export earnings) and survey the normative literature describing how SWFs should allocate funds. We then summarize the empirical literature studying how SWFs actually do allocate funds—across asset classes, geographically, and across industries. We document that most SWF equity investments in publicly traded firms involve cross‐border purchases of sizeable minority stakes (median around 20%) in target firms, with a strong preference for investments in the financial sector. Next, we assess empirical studies examining the impact of SWF stock investments on target firm financial and operating performance, and find universal support for a positive announcement period stock price increase of 1–3%. This, however, is significantly lower than the 5% abnormal return documented for stock purchases by comparable privately owned financial investors in recent studies, indicating a “sovereign wealth fund discount.” We conclude by summarizing the lessons of SWF research and pointing out unresolved issues.     

EDUCATION AND ENTREPRENEURSHIP SELECTION AND PERFORMANCE: A REVIEW OF THE EMPIRICAL LITERATURE

Abstract This paper provides a review of empirical studies into the impact of formal schooling on entrepreneurship selection and performance in industrial countries. We describe the main effects found in the literature, we explain the variance in results across almost a hundred studies, and we put the empirical results in the context of related economic theory and the much further developed literature in labor economics (studying the rate of return to education among wage employees). Five main conclusions result from this meta‐analysis. First, the impact of education on selection into entrepreneurship is insignificant. Second, the effect of education on performance is positive and significant. Third, the return to a marginal year of schooling is 6.1% for an entrepreneur. Fourth, the effect of education on earnings is smaller for entrepreneurs than for employees in Europe, but larger in the USA. Fifth, the returns to schooling in entrepreneurship are higher in the USA than in Europe, higher for females than for males, and lower for non‐whites or immigrants. In conclusion, we offer a number of suggestions to move the research frontier in this area of inquiry. The entrepreneurship literature on education can benefit from the technical sophistication used to estimate the returns to schooling for employees.     

TECHNOLOGICAL INNOVATION AND EMPLOYMENT IN DERIVED LABOUR DEMAND MODELS: A HIERARCHICAL META‐REGRESSION ANALYSIS

The effect of technological innovation on employment is of major concern for workers and their unions, policy makers and academic researchers. We meta‐analyse 570 estimates from 35 primary studies that estimate a derived labour demand model. We contribute to existing attempts at evidence synthesis by addressing the risks of selection bias and that of data dependence in observational studies. Our findings indicate that: (i) hierarchical meta‐regression models are sufficiently versatile for addressing both selection bias and data dependence in observational data; (ii) innovation's effect on employment is positive but small and highly heterogeneous; (iii) only a small part of residual heterogeneity is explained by moderating factors; (iv) selection bias tends to reflect preference for upholding prevalent hypotheses on the employment effects of process and product innovations; (v) country‐specific effect‐size estimates are related to labour market and product market regulation in six OECD countries in a U‐shaped fashion; and (vi) OLS estimates reflect upward bias whereas those based on time‐differenced or within estimators reflect a downward bias. Our findings point out to a range of data quality and modelling issues that should be addressed in future research.     

DOES EDUCATION REALLY IMPROVE HEALTH? A META‐ANALYSIS

While numerous studies assess the relationship between education and health, no consensus has been reached on whether education really improves health. We perform a meta‐analysis of 4866 estimates gleaned from 99 published studies that examine the health effects of education. We find that the current literature suffers from moderate publication bias towards the positive effects of education on health. After correcting for publication bias with an array of sophisticated methods, we find that the overall effect size is practically zero, indicating that education generates no discernible benefits to health. The heterogeneity analysis by Bayesian Model Averaging (BMA) and Frequentist Model Averaging (FMA) reveals that the reported estimates can be largely explained by whether the econometric models control for endogeneity of education, the types of data and the differences in health measurements. Our results also suggest that education may not be an effective policy option for promoting population health.     

HOW DO RATING AGENCIES’ DECISIONS IMPACT STOCK MARKETS? A META‐ANALYSIS

The purpose of this study is to examine how credit rating agencies’ decisions impact the stock market using a systematic and quantitative review of existing empirical studies. Specifically, we employ a meta‐regression analysis (MRA) to investigate the extent and nature of the effect of rating agencies’ decisions on the stock market. We survey 62 studies published between 1978 and 2015. Our first finding is that the cumulative average abnormal returns calculated from this empirical literature are affected by publication bias. After controlling for publication bias, the main findings of our meta‐analysis indicate that negative rating decisions cause statistically significant negative abnormal returns. This evidence suggests an informational effect. Our results also indicate that positive rating decisions do not have a significant effect. Finally, the MRA results reveal the importance of several factors related to primary study design, as well as to the nature of the data.     

政务信息化与地方政府预算资金使用效率

近年来信息化技术快速发展,与政务活动紧密结合,为提升政府预算资金使用效率创造了新契机。本文选取2016—2019年我国地级市面板数据,使用DEA-Tobit两步法分析政务信息化对地方政府预算资金使用效率的影响及其作用机理。研究发现：较高的政务信息化水平有助于地方政府预算资金使用效率的提升,且在国家审计功能效应强或是信任环境好的地区,政务信息化对地方政府预算资金使用效率的提升作用更加明显。作用机制分析表明,政务信息化可以通过提升财政透明度和公众关注度进而提升地方政府预算资金使用效率。最后,本文就地方政府如何提升预算资金使用效率提出一些政策建议,以期为政府相关部门提供有益参考。     

中国地方政府消费支出效率及其区域差距演化

本文利用两阶段研究框架分析分税制改革以来(1994～2006年)中国各省级政府消费支出的效率、区域差距演化及其影响因素.第一阶段,运用DEA非参数方法,以地区生产总值为产出,核算31个省(市、区)政府消费支出的效率得分,并描述支出效率的区域差距演化;第二阶段,利用面板数据受限Tobit模型,以各省(市、区)效率得分为因变量,分析政府消费支出效率区域差距演化的影响因素.结果表明,东部地区的政府消费支出效率显著强于中部和西部地区;区域间差距自分税制改革以来逐年缩小,尤其是东部和中部地区的效率差异在2006年前后已基本消失.区域间政府消费支出效率之所以出现了明显的趋同,既得益于中西部地方政府行政效率的提高,也得益于人力资本在区域间分布日趋平衡.     

Understanding variation in the relationship between environmental management practices and firm performance across studies: A meta‐analytic review

The relationship between environmental management practices and firm performance has continuously received much attention in academic research. As existing literature on the link of the two constructs is characterized by heterogeneous research characteristics and mixed empirical evidence, one interesting question arises: Do research characteristics affect the magnitude and direction of the relationship between environmental management practices and firm performance? Amassing a database of 92 studies, 199 effect sizes, and 72,258 firms, we examine this question by conducting a meta‐analysis. The characteristics investigated in this study include item number of performance measures, year of data collection, industry type, economic development, and Hofstede's five cultural dimensions. A meta‐regression reveals that environmental management practices are positively associated with firm performance and that the degree of this association depends on these contexts. Specifically, the environmental management practices–performance relationship increases with year of data collection, is stronger with multiple item measures, and is higher for firms in developed countries and in cultures characterized by high power distance, low individualism, low uncertainty avoidance, and low long‐term orientation.