Project evaluation and organizational form

In situations of imperfect testing and communication, as suggested by Sah and Stiglitz (AER, 1986), organizational forms can be identified with different rules of aggregating evaluations of individual screening units. In this paper, we discuss the relative merits of polyarchical organizations versus hierarchical organizations in evaluating cost-reducing R&D projects when individual units' decision thresholds are fully endogenous. Contrary to the results of Sah and Stiglitz, we find that the relative merit of an organizational form depends on the curvature of the screening functions of the individual evaluation units. We find that for certain parameters organizations would want to implement asymmetric decision rules across screening units. This allows us to derive sufficient conditions for a polyarchy to dominate a hierarchy. We also find conditions for which the cost curves associated with the two organizational forms cross each other. In this case the optimal organizational form will depend on product market conditions and on the “lumpiness” of cost-reducing R&D.     

The competitive firm under price uncertainty: the role of information and hedging

We study the impact of transparency in a commodity market on the decision problem of a competitive firm under price uncertainty and hedging opportunities. Market transparency is modeled by means of the informational content of publicly observable signals which are correlated with the random price. We find that the impact of more transparency on labor employment and production depends on the firm’s technology. In particular, more transparency may result in lower average output even though on average more labor has been used in the production process. We also analyze the link between market transparency and the welfare of the firm. We are grateful to two anonymous referees who made extremely useful comments and suggestions.     

Investment and Uncertainty: A Theory‐based Empirical Approach*

This paper provides empirical evidence on the dynamic effects of uncertainty on firm‐level capital accumulation. A novelty in this paper is that the firm‐level uncertainty indicator is motivated and derived from a theoretical model, the neoclassical investment model with time to build. This model also serves as the base for the empirical work, where an error‐correction approach is employed. I find a negative effect of uncertainty on capital accumulation, both in the short run and the long run. This outcome cannot be explained by the model alone. Instead, the results suggest that the predominant mechanism at work stems from irreversibility constraints.     

Maternal employment,migration, and child development

We analyze the roles of and interrelationships among school inputs and parental inputs in affecting child development through the specification and estimation of a behavioral model of household migration and maternal employment decisions. We integrate information on these decisions with observations on child outcomes over a 13-year period from the National Longitudinal Study of Youth (NLSY). We find that the impact of our school quality measures diminishes by factors of 2 to 4 after accounting for the fact that families may choose where to live in part based on school characteristics and labor market opportunities. The positive statistical relationship between child outcomes and maternal employment reverses sign and remains statistically significant after controlling for its possible endogeneity. Our estimates imply that when parental responses are taken into account, policy changes in school quality end up having only minor impacts on child test scores.     

Corporate financial determinants of foreign direct investment

Financial market incompleteness and (partial) segmentation of financial markets internationally may endow some firms with a financial advantage which can be exploited through foreign direct investment. We argue that this advantage appears as a distinct cost-of-capital effect on FDI, and identify possible channels for such an effect. Using a sample of European firms’ cross-border acquisitions, and controlling for traditional firm-level determinants of FDI, we find strong support for a cost-of-equity effect, whereas the effect of debt costs is indeterminate. Moreover, financial FDI determinants are more important for firms with high knowledge intensity and for firms resident in relatively less financially developed countries.     

A spatio-temporal model of house prices in the USA

This paper provides an empirical analysis of changes in real house prices in the USA using State level data. It examines the extent to which real house prices at the State level are driven by fundamentals such as real per capita disposable income, as well as by common shocks, and determines the speed of adjustment of real house prices to macroeconomic and local disturbances. We take explicit account of both cross-sectional dependence and heterogeneity. This allows us to find a cointegrating relationship between real house prices and real per capita incomes with coefficients (1,−1)$(1,-1)$, as predicted by the theory. We are also able to identify a significant negative effect for a net borrowing cost variable, and a significant positive effect for the State level population growth on changes in real house prices. Using this model we then examine the role of spatial factors, in particular, the effect of contiguous states by use of a weighting matrix. We are able to identify a significant spatial effect, even after controlling for State specific real incomes, and allowing for a number of unobserved common factors. We do, however, find evidence of departures from long run equilibrium in the housing markets in a number of States notably California, New York, Massachusetts, and to a lesser extent Connecticut, Rhode Island, Oregon and Washington State.     

A Simple Panel‐CADF Test for Unit Roots*

In this paper, we propose a simple extension to the panel case of the covariate‐augmented Dickey–Fuller (CADF) test for unit roots developed in Hansen (1995) . The panel test we propose is based on a P values combination approach that takes into account cross‐section dependence. We show that the test has good size properties and gives power gains with respect to other popular panel approaches. An empirical application is carried out for illustration purposes on international data to test the purchasing power parity (PPP) hypothesis.     

Estimation of stochastic frontier production functions with input-oriented technical efficiency

This paper deals with estimation of input-oriented (IO) technical inefficiency using a stochastic production frontier model. Econometrically the model is similar to a class of models that arise in specifying technical inefficiency in cost-minimizing and profit-maximizing frameworks. The standard maximum likelihood (ML) method that is used to estimate output-oriented (OO) technical efficiency cannot be applied to estimate these models. We use a simulated ML approach to estimate the IO production function and compare results from the IO and OO models, mainly to emphasize the point that estimated efficiency, returns to scale, technical change, etc., differ depending on whether one uses the model with IO or OO technical inefficiency.     

Identification in a model of sorting with social externalities and the causes of urban segregation

This paper discusses nonparametric identification in a model of sorting in which location choices depend on the location choices of other agents as well as prices and exogenous location characteristics. In this model, demand slopes and hence preferences are not identifiable without further restrictions because of the absence of independent variation of endogenous composition and exogenous location characteristics. Several solutions of this problem are presented and applied to data on neighborhoods in US cities. These solutions use exclusion restrictions, based on either subgroup demand shifters, the spatial structure of externalities, or the dynamics of prices and composition in response to an amenity shock. The empirical results consistently suggest the presence of strong social externalities, that is a dependence of location choices on neighborhood composition.     

“Waiting for Life to Arrive”: A history of the regression-discontinuity design in Psychology,Statistics and Economics

This paper reviews the history of the regression discontinuity design in three academic disciplines. It describes the design's birth and subsequent demise in Psychology even though most problems with it had been solved there. It further describes the scant interest shown in the design by scholars formally trained in Statistics, and the design's poor reception in Economics from 1972 until about 1995, when its profile and acceptance changed. Reasons are given for this checkered history that is characterized as waiting for life to arrive.     

Patent activity and technical change

As creations of the mind, intellectual property includes industrial property and copyrights. This paper presents an aggregate production function of the generalized Fechner–Thurstone (GFT) form to analyze the impact of an important component of intellectual industrial property, namely patent activity, on technical change in the USA for the period 1947–1981. Patents should alter isoquant maps, and measuring their elasticities is both intuitively and empirically appealing. We define a technology-changer as a variable that has an impact on the elasticity of the marginal rate of technical substitution (MRTS) between inputs of the GFT production function over time. Various types of US patent grant activity, specifically total, domestic, foreign, successful and unsuccessful patent applications, are used as instruments for the technology-changer. Using the GFT specification, the impacts of various technology-changers on the elasticity of the MRTS between inputs are estimated directly. It is found that granted (or successful) patents, patents granted to foreign companies and individuals, total patent applications, and even unsuccessful patent applications, have significant impacts on the rates at which inputs are substituted for each other over time in production.     

Cross‐sectional Dependency and Size Distortion in a Small‐sample Homogeneous Panel Data Unit Root Test*

In this paper, we investigate the effects of cross‐sectional disturbance correlation in a homogeneous panel data unit root test. As reported by other authors, the unit root test has incorrect size in the presence of cross‐sectional correlation. We suggest that a previously known estimator can be used to reduce the size distortions. We supply response surface estimates for critical values and study the size characteristics of the proposed test. We find that the suggested estimator performs well in small‐sample homogeneous panel data unit root tests. The reduction in size distortion comes at a small cost of lower power against a stationary alternative.     

Growth and convergence: A profile of distribution dynamics and mobility

In this paper we focus primarily on the dynamic evolution of the world distribution of growth rates in per capita GDP. We propose new concepts and measures of “convergence,” or “divergence” that are based on entropy distances and dominance relations between groups of countries over time.     

Horizontal vs. Vertical Interdependence in Multinational Activity*

This paper sheds light on interdependencies in multinational activity that are brought about by (horizontal) trade in final goods and (vertical) trade in intermediate goods (within and between host countries). We use a panel data set of US foreign affiliate sales to 16 developed countries in seven industries over the period 1983–2000, distinguish between horizontal and vertical interdependence in multinational enterprise activity and allow for both market size (demand)‐related as well as remainder linkage effects. Evidence suggests that vertical interdependence is somewhat more important than horizontal interdependence and, hence, vertical motives of multinational activity tend to dominate horizontal ones.

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Organizational design with a budget constraint

In this paper we point out that the presence of the budget constraint substantially affects the relative performance of organizational decision rules. For instance, if there are only two types of projects to decide upon, the hierarchy always performs better than the polyarchy. The same result holds for any distribution of the quality of projects. We also illustrate that optimal mechanisms for variable evaluation costs involve stopping rules which look hierarchical, but avoid costly duplication as in hierarchies or polyarchies. Received: 5 November 1995 / Accepted: 18 September 1997     

Multiplicative-error models with sample selection

This paper presents a simple approach to deal with sample selection in models with multiplicative errors. Models for non-negative limited dependent variables such as counts fit this framework. The approach builds on a specification of the conditional mean of the outcome only and is, therefore, semiparametric in nature. GMM estimators are constructed for both cross-section data and for panel data. We derive distribution theory and present Monte Carlo evidence on the finite-sample performance of the estimators.     

How to get firms to invest: A simple solution to the hold-up problem in regulation

Abstract. Many governmental programs are effective only if firms make costly investments. The inability of authorities to precommit to a regulatory scheme creates incentives for firms not to invest and to hold-up the regulator. This paper describes a simple subsidy/tax scheme embedded in a four-stage mechanism that solves the hold-up problem. We design a self-financing subsidy/tax scheme which benefits a complying firm at the expense of a non-complying firm. In order to be credible, the subsidy and tax rates must maximize social welfare for any combination of investment decisions. We show that there exists a unique subgame perfect equilibrium in which all firms invest and no actual implementation with subsidies and taxes is required. We discuss in which cases the mechanism can work under incomplete information. Received: 30 December 1998 / Accepted: 12 October 2001     

Inference with dependent data using cluster covariance estimators

This paper presents an inference approach for dependent data in time series, spatial, and panel data applications. The method involves constructing t and Wald statistics using a cluster covariance matrix estimator (CCE). We use an approximation that takes the number of clusters/groups as fixed and the number of observations per group to be large. The resulting limiting distributions of the t and Wald statistics are standard t and F distributions where the number of groups plays the role of sample size. Using a small number of groups is analogous to ‘fixed-b’ asymptotics of [Kiefer and Vogelsang, 2002] and [Kiefer and Vogelsang, 2005] (KV) for heteroskedasticity and autocorrelation consistent inference. We provide simulation evidence that demonstrates that the procedure substantially outperforms conventional inference procedures.     

Panel data models with spatially correlated error components

In this paper we consider a panel data model with error components that are both spatially and time-wise correlated. The model blends specifications typically considered in the spatial literature with those considered in the error components literature. We introduce generalizations of the generalized moments estimators suggested in Kelejian and Prucha (1999. A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40, 509–533) for estimating the spatial autoregressive parameter and the variance components of the disturbance process. We then use those estimators to define a feasible generalized least squares procedure for the regression parameters. We give formal large sample results for the proposed estimators. We emphasize that our estimators remain computationally feasible even in large samples.     

Identification of binary choice models with social interactions

This paper provides a set of results on the econometric identifiability of binary choice models with social interactions. Our analysis moves beyond parametric identification results that have been obtained in the literature to consider the identifiability of model parameters when the distribution of random payoff terms is unknown. Further, we consider how identification is affected by the presence of unobservable payoff terms of various types as well as identification in the presence of certain forms of endogenous group membership. Our results suggest that at least partial identification may be achieved under assumptions that in certain contexts may be plausible.