What Goes Up Might Not Come Down: Modeling Directional Asymmetry with Large-N, Large-T Data

Modeling asymmetric relationships is an emerging subject of interest among sociologists. York and Light advanced a method to estimate asymmetric models with panel data, which was further developed by Allison. However, little attention has been given to the large- N, large- T case, wherein autoregression, slope heterogeneity, and cross-sectional dependence are important issues to consider. The authors fill this gap by conducting Monte Carlo experiments comparing the bias and power of the fixed-effects estimator to a set of heterogeneous panel estimators. The authors find that dynamic misspecification can produce substantial biases in the coefficients. Furthermore, even when the dynamics are correctly specified, the fixed-effects estimator will produce inconsistent and unstable estimates of the long-run effects in the presence of slope heterogeneity. The authors demonstrate these findings by testing for directional asymmetry in the economic development–CO2 emissions relationship, a key question in macro sociology, using data for 66 countries from 1971 to 2015. The authors conclude with a set of methodological recommendations on modeling directional asymmetry.

Non-Neutral Marginal Innovation Costs, Omitted Variables, and Induced Innovation

Prior tests of Hicks’ Induced Innovation Hypothesis (IIH) have been greatly hampered because the lack of supply-side data implicitly requires the untenable assumption that the marginal research cost is the same for different inputs. We document that, with appropriate model specification and panel data, a two-way fixed-effects estimator can account for much of the non-neutrality of the innovation function. Using a test procedure that is robust to a time-variant and non-neutral innovation function, we test the IIH in U.S. agriculture for the period 1960–2004. We use only readily available data for innovation demand and total public research expenditures.

Capital adjustment cost and inconsistency in income-based dynamic panel models with fixed effects

After the seminal work of Nickell (1981), a vast literature demonstrates the inconsistency of ‘conditional convergence’ estimator in income-based dynamic panel models with fixed effects when the time horizon (T) is short but the sample of countries (N) is large. Less attention is given to the economic root of inconsistency of the fixed effects estimator when T is also large. Using a variant of the Ramsey growth model with long-run adjustment cost of capital, we demonstrate that the fixed effects estimator of such models could be inconsistent when T is large. This inconsistency arises because of the long-run adjustment cost of capital which gives rise to a negative moving average coefficient in the error term. Income convergence will be thus overestimated. We theoretically characterize the order of this inconsistency. Our Monte Carlo simulation demonstrates that the size of the bias is substantial and it is greater in economies with higher capital adjustment costs. We show that the use of instrumental variables that take into account the presence of the negative moving average term in the error will overcome this bias.

Political Elites, Democracy, and Education

We identify conditions under which the political elite may overcompensate for the loss of de jure power by investing too much in de facto power so that the probability to have de facto power is higher under democracy than under nondemocracy. Then, we consider education and show that, under certain assumptions, the political elite may treat democracy and spending on citizens’ education as substitutes. Using African data and a fixed-effects estimator, we obtain empirical evidence in support of this theoretical prediction.

Not so Harmless After All: The Fixed-Effects Model

The fixed-effects estimator is biased in the presence of dynamic misspecification and omitted within variation correlated with one of the regressors. We argue and demonstrate that fixed-effects estimates can amplify the bias from dynamic misspecification and that with omitted time-invariant variables and dynamic misspecifications, the fixed-effects estimator can be more biased than the ‘naïve’ OLS model. We also demonstrate that the Hausman test does not reliably identify the least biased estimator when time-invariant and time-varying omitted variables or dynamic misspecifications exist. Accordingly, empirical researchers are ill-advised to rely on the Hausman test for model selection or use the fixed-effects model as default unless they can convincingly justify the assumption of correctly specified dynamics. Our findings caution applied researchers to not overlook the potential drawbacks of relying on the fixed-effects estimator as a default. The results presented here also call upon methodologists to study the properties of estimators in the presence of multiple model misspecifications. Our results suggest that scholars ought to devote much more attention to modeling dynamics appropriately instead of relying on a default solution before they control for potentially omitted variables with constant effects using a fixed-effects specification.

Getting the Within Estimator of Cross-Level Interactions in Multilevel Models with Pooled Cross-Sections: Why Country Dummies (Sometimes) Do Not Do the Job

Multilevel models with persons nested in countries are increasingly popular in cross-country research. Recently, social scientists have started to analyze data with a three-level structure: persons at level 1, nested in year-specific country samples at level 2, nested in countries at level 3. By using a country fixed-effects estimator, or an alternative equivalent specification in a random-effects framework, this structure is increasingly used to estimate within-country effects in order to control for unobserved heterogeneity. For the main effects of country-level characteristics, such estimators have been shown to have desirable statistical properties. However, estimators of cross-level interactions in these models are not exhibiting these attractive properties: as algebraic transformations show, they are not independent of between-country variation and thus carry country-specific heterogeneity. Monte Carlo experiments consistently reveal the standard approaches to within estimation to provide biased estimates of cross-level interactions in the presence of an unobserved correlated moderator at the country level. To obtain an unbiased within-country estimator of a cross-level interaction, effect heterogeneity must be systematically controlled. By replicating a published analysis, we demonstrate the relevance of this extended country fixed-effects estimator in research practice. The intent of this article is to provide advice for multilevel practitioners, who will be increasingly confronted with the availability of pooled cross-sectional survey data.

Corporate governance: evidence from Islamic banks

Purpose This paper aims to examine the impact of Shari’ah supervisory boards (SSBs) on the performance of Islamic banks (IBs). It also tests whether SSBs’ attributes affect the performance of IBs. Based on a sample of 1,803 Islamic bank-year observations from 82 banks in 15 countries over the period 1993-2014 and controlling for factors known to affect bank performance, this study reveals a robust and significant positive relationship between SSBs and Islamic bank performance. This study also shows that the characteristics of SSBs affect the performance of IBs. This research reveals how SSBs influence the performance of IBs, as well as the processes and roles SSBs use to ensure Shari’ah compliance in business transactions. Design/methodology/approach The purpose of this study design is to relate SSB presence, size and diversity to financial performance using three techniques. The first technique is a multivariate data analysis that analyzes data arising from more than one variable. The second technique is a clustered regression (clustering by bank), which corrects for serial correlation and produces unbiased t-statistics. Because this sample is drawn from panel data, it is expected serial autocorrelation of the independent variables and error term within banks. In cases where within-company correlation exists, t-statistics based on average regression coefficients from year-by-year regression are upwardly biased and potentially severe (Peterson, 2009). Therefore, this study uses a technique that agrees with Stock and Watson (2002), who show that the standard method of calculating heteroskedasticity-robust standard errors for the fixed-effects estimator generates inconsistent variance estimates. Thus, using the clustered regression is consistent with the fixed-effects estimator. The third technique is a two-stage least-squares regression that helps build an instrumental variable for robustness tests purposes. Findings The findings suggest that large corporate boards and large SSBs are more efficient in dealing with different monitoring and advisory roles than small SSBs. Consequently, this suggests that increasing the size of corporate boards and SSBs should improve monitoring and advisory functions, management behavior and organizational performance. Research limitations/implications It is possible that there is an upper limit to this benefit, however; we do not explore this limit, which therefore provides opportunities for additional research. Because Shari’ah compliance relates only to a rational legal framework of negative screening relegated to interest prohibition and limiting uncertainty. The interest prohibition and limiting uncertainty have not been investigated between the two samples due to data unavailability. In addition, limited accounting-based measures of financial performance may not accurately portray IB performance; hence, an additional market measure is implemented, which is Tobin’s Q. Practical implications Ultimately, these findings could help IBs improve their financial results by enhancing their internal and external governance mechanisms (Walsh and Seward, 1990). They provide a basis for developing larger, more diverse SSBs that are more focused on complying with Shari’ah and corporate governance. The results also have significant policy implications for improving firm-level corporate governance versus improving country-level institutional factors. Both views have their advocates. However, it is very difficult to reform the legal system in a short time. Still, this study shows that struggling IBs have a way to improve their corporate governance and simultaneously improve their financing environment. Originality/value This research contributes to the literature on the effects of SSBs on IBs’ organizational financial performance, processes and roles. It is the first to examine empirically the underpinnings of how SSBs affect organizational financial performance via agency theory and contingency theory.

Local Semi-Parametric Efficiency of the Poisson Fixed Effects Estimator

Hausman, Hall, and Griliches [Hausman, J., H. B. Hall, and Z. Griliches. 1984. “Econometric Models for Count Data with an Application to the Patents-R & D Relationship.”