Wage differentials in the presence of unobserved worker,firm, and match heterogeneity

We consider the problem of estimating and decomposing wage differentials in the presence of unobserved worker, firm, and match heterogeneity. Controlling for these unobservables corrects omitted variable bias in previous studies. It also allows us to measure the contribution of unmeasured characteristics of workers, firms, and worker-firm matches to observed wage differentials. An application to linked employer-employee data shows that decompositions of inter-industry earnings differentials and the male-female differential are misleading when unobserved heterogeneity is ignored.     

Identification of first-price auctions with non-separable unobserved heterogeneity

We propose a novel methodology for identification of first-price auctions, when bidders’ private valuations are independent conditional on one-dimensional unobserved heterogeneity. We extend the existing literature ( and ) by allowing the unobserved heterogeneity to be non-separable from bidders’ valuations. Our central identifying assumption is that the distribution of bidder values is increasing in the state. When the state-space is finite, such monotonicity implies the full-rank condition needed for identification. Further, we extend our approach to the conditionally independent private values model of Li et al. (2000), as well as to unobserved heterogeneity settings in which the implicit reserve price or the cost of bidding varies across auctions.     

Global public spending efficiency in Tuscan municipalities

The paper presents a Data Envelopment Analysis aimed at studying the efficiency of Tuscan municipalities' public expenditure. Five strategic functions of Tuscan municipalities are first considered carrying out a non-aggregate analysis; then the overall expenditure composition of each municipality and the global spending efficiency are analysed by a proposed composite indicator. The main determinants affecting the municipalities' efficiency were further investigated. In particular, the obtained results may be consistently included in the long-standing debate on the municipal size, proving that the bigger the municipality, the greater its level of public expenditure efficiency.     

Testing for unobserved heterogeneity in exponential and Weibull duration models

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chi-square, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter value on the boundary of the parameter space, as in Cho and White (2007a). We accommodate these and provide methods delivering consistent asymptotic critical values. We conduct a number of Monte Carlo simulations, comparing the level and power of the LR test statistic to an information matrix (IM) test due to Chesher (1984) and Lagrange multiplier (LM) tests of Kiefer (1985) and Sharma (1987). Our simulations show that the LR test statistic generally outperforms the IM and LM tests. We also revisit the work of van den Berg and Ridder (1998) on unemployment durations and of Ghysels et al. (2004) on interarrival times between stock trades, and, as it turns out, affirm their original informal inferences.     

Identification in nonparametric limited dependent variable models with simultaneity and unobserved heterogeneity

We extend the identification results for nonparametric simultaneous equations models in Matzkin (2008) to situations where the observations on the vector of dependent variables might be limited, and where the number of exogenous unobservable variables is larger than the number of dependent variables.     

Output complexity, environmental conditions, and the efficiency of municipalities

Over the last few years, many studies have analyzed the efficiency of local governments in different countries. An accurate definition of their output bundles—i.e., the services and facilities they provide to their constituencies—is essential to this research. However, several difficulties emerge in this task. First, since in most cases the law only establishes the minimum amount of services and facilities to provide, it may well be the case that some municipalities go beyond the legal minimum and, consequently, might have an uncertain effect on efficiency when compared to other municipalities which stick to the legal minimum. Second, municipalities face very different environmental conditions, which raises some doubts about the plausibility of an unconditional analysis. This study tackles these problems by proposing an analysis in which the efficiency of municipalities is evaluated after splitting them into clusters according to various criteria (output mix, environmental conditions, level of powers). We perform our estimations using order-m frontiers, given their robustness to outliers and immunity to the curse of dimensionality. We provide an application to Spanish municipalities, and results show that both output mix and, more especially, environmental conditions, should be controlled for, since efficiency differences between municipalities in different groups are notable.     

Measuring efficiency in the presence of head-to-head competition

We develop a new DEA model that measures organizational efficiency in the presence of head-to-head competition. Our model differs from existing DEA models that ignore competition (or any other form of interaction) among the organizations under analysis. The model assumes that organizations deploy inputs for the explicit purpose of increasing its own outputs while reducing the outputs of its competitors. We apply this model to the 2002, 2004, and 2006 political campaigns in New York State for the US. House of Representatives in which candidates spent money to increase the number of votes that they received and decrease the number of votes that their opponents received. We show that campaign inefficiency can alter the outcome of an election. Specifically, a loser would have won in six of the 57 races had he or she been efficient. We also show that incumbents are more likely to spend inefficiently than are challengers. Overall, inefficiency accounts for less than 5% of campaign funding but a loss of about 9% in votes received. We find evidence that campaign efficiency has increased since the passage of the Bipartisan Campaign Reform Act of 2002, known widely as the McCain-Feingold Act.     

Testing the proportional hazards assumption in the presence of unmeasured heterogeneity

This paper develops a discrete-time hazard model which accounts for unmeasured hetergeneity while allowing the coefficients of the regressors to vary over time. Sufficient conditions for nonparametric identifiability of the unmeasured heterogeneity distribution are derived. Testing for time-varying coefficients in this model is, under suitable conditions, equivalent to testing the proportionality assumption of the underlying continuous-time hazard model. Some Monte Carlo evidence is presented regarding the small-sample properties of this test. As an illustration, these tests are applied to the joblessness durations of displaced workers.     

The (mis)specification of discrete duration models with unobserved heterogeneity: A Monte Carlo study

Empirical researchers usually prefer statistical models that can be easily estimated with the help of commonly available software packages. Sequential binary models with or without normal random effects are an example of such models that can be adopted to estimate discrete duration models with unobserved heterogeneity. But an easy-to-implement estimation may incur a cost. In this paper we conduct a Monte Carlo simulation to evaluate the consequences of omitting or misspecifying the unobserved heterogeneity distribution in single-spell discrete duration models.     

Foreign presence and efficiency in transition economies

This paper presents empirical evidence on the role of foreign presence in the performance of domestic manufacturing firms in five Central and Eastern European countries. Data Envelopment Analysis (DEA) was used to estimate a frontier for each sector with similar technology common for five transition countries in the sample − Bulgaria, Estonia, Hungary, Poland and Romania. Following Simar and Wilson (J Econom 136(1):31–64, 2007), this study applies a truncated regression and bootstrap technique in a second stage post-DEA analysis. Some evidence is found to support the hypothesis that foreign presence has an overall positive spillover effects on the performance of domestic firms.     

Evaluating food retailing efficiency: the role of information technology

Information and internet-based technologies have fostered new supply chain initiatives in food retailing but little research has evaluated performance and efficiency impacts. A distance function based on three key performance measures for food retailers is used to evaluate store performance and efficiency. The effects of store format, membership in a chain, unionization, and the adoption of a variety of information technologies. Supply chain technologies are groups into three general categories including data sharing technologies, decision sharing technologies, and technologies that support product assortment, pricing, and merchandising decisions.      

Management in production: from unobserved to observed

Are productivity estimates good proxies for unobserved management? And, does management affect production in a neutral and monotonic fashion as assumed by these proxies? We use Bloom and Van Reenen’s management data to show that two popular proxies, fixed effects and inefficiency scores, correlate with observed management practices. We find that the correlations are positive but weak. Also, management explains only a fraction of the proxies’ variances. The data rejects the assumptions of neutrality and monotonicity. Last, our results suggest that management has characteristics both of a technology and an input.     

Tourism competitiveness of Italian municipalities

Quality & Quantity - The purpose of the paper is the study of tourism competitiveness and its determinants for the almost 8000 Italian municipalities. The partial least squares method...     

An application of model-based estimation of unobserved components

The paper analyzes a real-world application of an ARIMA-based trend/seasonal/irregular estimation. The analysis illustrates two points of applied interest. First, it is seen how the decomposition of ARIMA models is sensitive to changes in the specification of the overall model. Alternative ARIMA models, which yield similar fits and forecasts, may produce remarkably different decompositions. Second, it is shown how the model-based approach provides tools for interpretation of the results. In particular, the comparison between the empirical autocorrelation of the estimated components and the theoretical autocorrelations of the model-based estimators can be used as an overall diagnostic check.     

Farm heterogeneity and technical efficiency: Some results from Swedish dairy farms

This paper introduces farm-heterogeneity in measuring technical efficiency of Swedish dairy farms using farm-level data. In calculating technical efficiency which is allowed to vary over time and across farms, we control for farm-specific effects. This is possible only when panel data is available. Furthermore, we separate technical efficiency from technical change—the presence of which is indicated by a shift in the production function over time,ceteris paribus. We also calculate percentage change in technical efficiency to examine whether farm efficiencies have improved over time. Finally, a comparison of technical efficiency, elasticities of different inputs, and technical change is made across different years and panels. The data includes four panels of dairy farms observed during the period 1976–1988, excluding 1985.We thank two anonymous referees, Anders Klevmarken and Lennart Hjalmarsson for valuable comments. Financial support from SJFR, the Gothenburg Economic School Foundation, Jan Wallender and Tore Browaldh Research Foundations is gratefully acknowledged.     

A multivariate unobserved component analysis of US housing market

This study explores price dynamics and price relationships in the US housing market with a focus on four regions: Northeast, Midwest, South, and West. It applies a multivariate state-space model to identify the common trends and common cycles in US regional markets. The study finds that the principal source of secular price variability in the Northeast and West markets is due to two common stochastic trends, while a large share of transitional price variability in the Northeast, West and Midwest originates from three common stochastic cycles. The study estimates the relationships between the common unobserved components and economic variables and finds that unemployment, federal funds rate, corporate default risk, economic expansion, unanticipated inflation in the construction market are significant underlying economic phenomena that impact the evolution of the common movements in both the short run and the long run housing dynamics. Authorship is equally shared between the authors.     

Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach

This paper investigates the productivity and efficiency of large bank holding companies (BHCs) in the United States over the period 2004–2013, by estimating a translog stochastic distance frontier (SDF) model with time-varying heterogeneity. The main feature of this model is that a multi-factor structure is used to disentangle time-varying unobserved heterogeneity from inefficiency. Our empirical results strongly suggest that unobserved heterogeneity is not only present in the U.S. banking industry, but also varies over time. Our results from the translog SDF model with time-varying heterogeneity show that the majority of large BHCs in the U.S. exhibit increasing returns to scale, a small percentage exhibit constant returns to scale, and an even smaller percentage exhibit decreasing returns to scale. Our results also show that on average the BHCs have experienced small positive or even negative technical change and productivity growth.     

Evaluating cost efficiency and returns to scale in the Life Insurance Corporation of India using data envelopment analysis

This paper applies a new variant of data envelopment analysis model to examine the performance of Life Insurance Corporation (LIC) of India. The findings show a significant heterogeneity in the cost efficiency scores over the course of 19 years. A decline in performance after 1994-1995 can be taken as evidence of increasing allocative inefficiencies arising from the huge initial fixed cost undertaken by LIC in modernizing its operations. A significant increase in cost efficiency in 2000-2001 is, however, cause for optimism that LIC may now be realizing a benefit from such modernization. This will stand them in good stead in terms of future competition. Results from a sensitivity analysis are in broad agreement with the main findings of this study.