APPLICATION OF PANEL DATA MODELS IN BENCHMARKING ANALYSIS OF THE ELECTRICITY DISTRIBUTION SECTOR*

ABSTRACT ** : This paper explores the application of several panel data models in measuring productive efficiency of the electricity distribution sector. Stochastic Frontier Analysis has been used to estimate the cost‐efficiency of 59 distribution utilities operating over a nine‐year period in Switzerland. The estimated coefficients and inefficiency scores are compared across three different panel data models. The results indicate that individual efficiency estimates are sensitive to the econometric specification of unobserved firm‐specific heterogeneity. This paper shows that alternative panel models such as the ‘true’ random effects model proposed by Greene (2005) could be used to explore the possible impacts of unobserved firm‐specific factors on efficiency estimates. When these factors are specified as a separate stochastic term, the efficiency estimates are substantially higher suggesting that conventional models could confound efficiency differences with other unobserved variations among companies. On the other hand, refined specification of unobserved heterogeneity might lead to an underestimation of inefficiencies by mistaking potential persistent inefficiencies as external factors. Given that specification of inefficiency and heterogeneity relies on non‐testable assumptions, there is no conclusive evidence in favour of one or the other specification. However, this paper argues that alternative panel data models along with conventional estimators can be used to obtain approximate lower and upper bounds for companies' efficiency scores.     

TESTING THE STRUCTURE OF CONDITIONAL CORRELATIONS IN MULTIVARIATE GARCH MODELS: A GENERALIZED CROSS‐SPECTRUM APPROACH*

We introduce a class of generally applicable specification tests for constant and dynamic structures of conditional correlations in multivariate GARCH models. The tests are robust to the presence of time‐varying higher‐order conditional moments of unknown form and are pure significance tests. The tests can identify linear and nonlinear misspecifications in conditional correlations. Our approach does not necessitate a particular parameter estimation method and distributional assumption on the error process. The asymptotic distribution of the tests is invariant to the uncertainty in parameter estimation. We assess the finite sample performance of our tests using simulated and real data.     

Rational Speculative Bubbles: An Empirical Investigation of the London Stock Exchange

In recent years, a sharp divergence of London Stock Exchange equity prices from dividends has been noted. In this paper, we examine whether this divergence can be explained by reference to the existence of a speculative bubble. Three different empirical methodologies are used: variance bounds tests, bubble specification tests, and cointegration tests based on both ex post and ex ante data. We find that, stock prices diverged significantly from their fundamental values during the late 1990's, and that this divergence has all the characteristics of a bubble.     

Semi-parametric models for satisfaction with income

An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables. In particular, limited dependent variable models that generalize ordered probit are compared to regression models that generalize the linear model. These techniques are then applied to analyze how self-reported satisfaction with household income relates to household income, family composition, and other background variables. Data are drawn from the 1998 wave of the German Socio-Economic Panel. The results are used to estimate equivalence scales and the cost of children. We find that the standard ordered probit model is rejected, while some semi-parametric specifications survive specification tests against nonparametric alternatives. The estimated equivalence scales, however, are often similar for the parametric and semi-parametric specifications.JEL Classification: C14, C35, D12Correspondence to: Charles BellemareWe are grateful to an anonymous referee and to participants of a CeMMAP/ESG workshop at University College London and seminars at CentER (Tilburg University) and Humboldt University Berlin for useful comments.     

A note on the Wald,LR and LM tests and misspecification

In this note, we investigate sensitivity of the Wald, LR and LM tests to specification error. It is shown that these three tests are very sensitive to specification error, but the LM test is relatively superior to other two tests under certain situations.     

Explaining the spatial variation in housing prices: an economic geography approach

This study is concerned with the validation of parametric functional representations of the conditional mean of wages using Philippine data. This is done in the light of studies confirming relative weaknesses associated with parametric approaches to the modelling of human capital earnings functions (Zheng, 2000; Heckman et al., 2003; Lemieux, 2003; Miles and Mora, 2003). Extending the approaches in Lemieux (2003), Zheng (2000) and Miles and Mora (2003), we conduct consistent specification tests not only on parametric functional forms but also on the semiparametric partially linear model to verify the effect of modelling choice on the schooling-earnings as well as the experience-earnings relationships. Test results indicate that parametric models may still be valid representations of the wage function. In some instances, the semiparametric partially linear wage function holds promise as a modelling alternative to parametric models.     

Health care utilization and self-assessed health: specification of bivariate models using copulas

The discernment of relevant factors driving health care utilization constitutes one important research topic in health economics. This issue is frequently addressed through specification of regression models for health care use (y—often measured by number of doctor visits) including, among other covariates, a measure of self-assessed health (sah). However, the exogeneity of sah within those models has been questioned, due to the possible presence of unobservables influencing both y and sah, and because individuals’ health assessments may depend on the quantity of medical care received. This article addresses the possible simultaneity of (sah, y) by adopting a full information approach, through specification of the bivariate probability function (p.f.) of these discrete variables, conditional on a set of exogenous covariates (x). The approach is implemented with copula functions, which afford separate consideration of each variable margin and their dependence structure. The specification of the joint p.f. of (sah, y) enables estimation of several quantities of potential economic interest, namely features of the conditional p.f. of y given sah and x. The adopted models are estimated through maximum likelihood, with cross-sectional data from the Portuguese National Health Survey of 1998–1999. Estimates of the margins’ parameters do not vary much among different copula models, while, in accordance with theoretical expectations, the dependence parameter is estimated to be negative across the various joint models.     

Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect

Over the past few decades, much progress has been made in semiparametric modelling and estimation methods for econometric analysis. This paper is concerned with inference (i.e. confidence intervals and hypothesis testing) in semiparametric models. In contrast to the conventional approach based on t‐ratios, we advocate likelihood‐based inference. In particular, we study two widely applied semiparametric problems, weighted average derivatives and treatment effects, and propose semiparametric empirical likelihood and jackknife empirical likelihood methods. We derive the limiting behaviour of these empirical likelihood statistics and investigate their finite sample performance through Monte Carlo simulation. Furthermore, we extend the (delete‐1) jackknife empirical likelihood toward the delete‐d version with growing d and establish general asymptotic theory. This extension is crucial to deal with non‐smooth objects, such as quantiles and quantile average derivatives or treatment effects, due to the well‐known inconsistency phenomena of the jackknife under non‐smoothness.     

Testing Multiple Non-Nested Factor Demand Systems

This article explains how to obtain straightforward extensions of the most popular univariate non‐nested statistics, and of the RESET‐test, to a multivariate context and examines how to use these tests to compare alternative factor demand systems. The empirical application involves the classical Berndt–Khaled KLEM data set. A statistically adequate specification is determined for each competing factor demand system. The empirical results are interpreted for each system, the models are compared on the basis of multivariate paired and joint non‐nested procedures and practical indications about what to expect if these tests are applied to alternative factor demand specifications are provided.     

Dynamic specification and misspecification in systems of demand equations: a testing strategy for model selection

The purpose of this study is to describe a misspecification testing strategy that is designed to ensure the appropriateness of the statistical assumptions underlying a system of equations. A systemwise test approach is used to test the statistical assumptions. The systemwise tests take into account information in, and interaction between, all equations in the system and can be used in a wide variety of applications where systems of equations are estimated. If the systemwise test leads to rejection, single equation F-test will then be used to help identify specific problems. The systemwise testing approach is illustrated by modelling Swedish consumer demand for milk. The example illustrates how the approach can be used to solve issues regarding dynamic specification of models, structural change and other forms of model misspecification.     

THE REGULATION OF MIGRATION IN A TRANSITION ECONOMY: CHINA'S HUKOU SYSTEM

Unlike most countries, China regulates internal migration. Access to public schools, health services, low‐cost housing, and attractive jobs by those who do not have local registration (Hukou) is often limited. Coincident with the deepening of economic reforms, Hukou has gradually been relaxed since the 1980s, contributing to a migration surge. In this study of interprovincial Chinese migration, we address two questions. First, what is a sensible way of incorporating Hukou into theoretical and empirical models of migration in China? Second, to what extent has Hukou influenced the scale and structure of migration? We incorporate two different measures of Hukou into a modified gravity model nuanced to fit the Chinese case: (1) the migrant's perceived probability of securing Hukou and (2) the perceived joint probability of securing Hukou and a job available only to a registered person. Our tests include a much wider variety of controls especially important for the Chinese case. Using census data for 1985–90, 1995–2000, and 2000–05, we find that migration is very sensitive to Hukou, with the greatest sensitivity occurring during the middle period. (JEL J61)     

INTERACTIONS BETWEEN WELFARE CASELOADS AND LOCAL LABOR MARKETS

This paper provides an empirical examination of interactions between welfare caseloads and local labor markets using data on caseload stocks, entries, and exits. Granger‐causality tests show that unemployment rates Granger‐cause caseload activity but caseload activity does not Granger‐cause unemployment rates. The results also reveal differential dynamics between caseloads and labor market conditions for rural versus metropolitan markets. Several models of one‐way association between caseload activity and unemployment rates are presented. The results show that higher unemployment rates are positively associated with welfare caseloads and entries and negatively related to exits. (JEL I38, R23)     

Ex post adaptations and hybrid contracts in software development services

We follow the recent literature on ex post adaptations in procurement and argue that highly volatile specifications result in multiple variations of fixed price (FP) and time and materials (T&M) contracts. Specifically, placing a cap on specification change in FP contracts prevents specification volatility, similar to the way that placing a cap on the price in T&M contracts prevents price escalation. We argue that these hybrid mechanisms are particularly important in software development contracting, a new critical business capability involving frequent and costly ex post adaptations to specification change. The level of completeness in these contractual archetypes is hypothesized to be determined by contracting costs and benefits, where costs are related to project uncertainty and benefits are related to the likelihood of vendor opportunism. We test this hypothesis with a unique data set of 270 software development contracts entered into by a leading international bank. The analysis confirms the existence of multiple hybrid contracts that mitigate both price escalation and specification volatility. It also shows that contracting costs and benefits explain more variance in contract choice when these hybrids are included, uncovering the detailed mechanisms used to curb opportunism when the vendor is less familiar to the client.     

TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N →∞ simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro‐panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over‐rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (≤10).     

WHO BENEFITS FROM PRICING REGULATIONS WHEN ECONOMIC SPACE MATTERS?

Reinterpreting Hwang‐Mai (AER, 1990) by both simplifying and generalizing their analysis in terms of two key demand parameters representing income and market size, we probe the welfare effects of spatial price discrimination to determine how robust the previous welfare findings in the literature are. Endogenous location matters when a monopolist chooses asymmetric location under different pricing schemes. If he/she remained at the same location, outcomes of fixed and endogenous location models must be analytically the same. Endogenous and different location changes outcomes radically. When non‐discriminatory pricing regulations benefit the poor, different transportation burdens mean that the rich become poor, even worse off than the ex‐poor, and the society becomes worse off accordingly.     

WIC PARTICIPATION AND MATERNAL BEHAVIOR: BREASTFEEDING AND WORK LEAVE

We examine the effects of the Women, Infants, and Children (WIC) Program on breastfeeding outcomes and maternal employment decisions. This research expands the existing literature using an alternative identification strategy and a broader set of outcomes. Using data from the Infant Feeding Practices Study II, we control for selection bias into WIC using the variation in food prices as an instrumental variable. The results of this study are robust to a number of specification and falsification tests. We find WIC decreases exclusive breastfeeding by nearly 50% and increases work leave duration by over 20%. (JEL I18, I38)     

Exogeneity of Money and its Policy Implications for Price Control: Evidence from South Asia

Abstract. We investigate the policy role that could be assigned to money stock in controlling the price level in four South Asian countries, namely, India, Nepal, Pakistan and Sri Lanka. The problem of policy assignment associated with the Granger non‐causality tests is pointed out. Various forms of exogeneity are tested. Money stocks (M₁ and M₂), consumer price index (CPI) and real GDP are cointegrated and causally related but we find overwhelming evidence of endogeneity of money. The endogeneity of money does not support the authorities’ policy stance of controlling price level through the control of money stock.     

Second thoughts on the exporter productivity premium

Abstract Contrary to the prevailing interpretation, this paper shows that the central models of trade with heterogeneous firms ( Melitz 2003 ; Bernard et al. 2003 ) exhibit ambiguous predictions for the exporter productivity premium. This prospect arises because of differences between theoretical and empirical representations of firm productivity. Instead of marginal productivity, we examine in both models the theoretical equivalent of empirically observable productivity (value‐added per employee). Given the presence of fixed export costs or heterogeneous mark‐ups and trade costs, the observable productivity of exporters in proximity to the export‐indifferent firm turns out to be lower than that of non‐exporters; that is, the productivity distributions overlap. The paper reviews empirical literature that reports non‐positive exporter productivity premia in firm‐level data and discusses implications for empirical research on exporter performance, including learning and the role of non‐parametric regressions (stochastic dominance, quantile regressions), fixed costs, and productivity distributions.     

Portfolio allocation and international risk sharing

Abstract We show that recent explanations of the consumption‐real exchange rate anomaly that rely on goods and financial market frictions are not robust to introducing just one additional international asset. When portfolios are selected optimally, international trade in two nominal bonds implies a consumption‐real exchange rate correlation that is too high compared with the data even when there are many shocks. Monetary policy specification plays a potentially important role for the degree of risk sharing provided by nominal bonds, both in the benchmark model with only tradable and non‐tradable sector supply shocks and also in the model that allows for news.     

On Optimal Instrumental Variables Generators, with an Application to Hedge Fund Returns

In this paper, we propose a new benchmarking procedure lying on cumulants for computing the factor loadings in financial models of returns. We apply this technique to the well-known augmented Fama and French (J Fin Econ 43(2):153–193, 1997) model and compare it with another technique of ours based on higher moments. Our new procedure confirms the fact that the alpha is supposed to decrease when we disaggregate HFR indices to the level of individual funds while correcting for specification errors. Our new technique is therefore useful for hedge funds selection or ranking based on the alpha of Jensen corrected for specification errors. This technique will also be useful for calibrating other financial models of returns like the simple market model or the conditional alpha and beta models.