Another look at the estimation of dynamic programming models with censored decision variables

In this paper we propose a new approach to estimate the structural parameters in the context of a censored continuous decision model. Instead of handling with the original model, we consider an approximate model in which the decision variable has been discretized in a finite number of values. In this sense, an ordered choice model becomes a natural approximation to an underlying and more complicated censored continuous one. We extend the kind of Hotz-Miller estimators proposed for the estimation of binary or multinomial choice models to the context of ordered choice models. The estimation approach is based on the existence of a one-to-one mapping from conditional choice value functions to conditional choice probabilities. Exploiting the invertibility of that mapping it is possible to obtain structural parameter estimates without solving the dynamic programming problem

Pseudo-maximum likelihood estimation of a dynamic structural investment model

This paper belongs to the recent investment literature focused on the modelling of microeconomic investment decisions. The increasing concern about this topic is related to the growing availability of microeconomic datasets which show the investment behavior taking place at the firm level. This behavior is far from the smooth capital adjustment pattern derived from the traditional investment models. Rather it is characterized by infrequent and lumpy adjustment. New investment models must be considered to capture this behavior. In this paper we formulate a dynamic structural investment model with irreversibility and nonconvex adjustment costs and try to stress the importance of these costs in the firms' investment decisions. From the methodological point of view, we set the investment decision on the dynamic programming framework. More specifically, we consider a discrete choice dynamic programming problem in which firms decide to invest or not to invest. The estimation strategy we adopt is the Nested Pseudo-Likelihood (NPL) algorithm recently proposed by Aguirregabiria and Mira (2002). It is an estimation method which has clear advantages over previous techniques proposed in this context. Up to our knowledge, this paper constitutes the first empirical application of this estimation method

Estimation of a dynamic discrete choice model of irreversible investment

In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem

ANOTHER LOOK AT THE ESTIMATION OF DYNAMIC PROGRAMMING MODELS WITH CENSORED DECISION VARIABLES

In this paper we propose a new approach to estimate the structural parameters in the context of a censored continuous decision model. Instead of handling with the original model, we consider an approximate model in which the decision variable has been discretized in a finite number of values. In this sense, an ordered choice model becomes a natural approximation to an underlying and more complicated censored continuous one. We extend the kind of Hotz-Miller estimators proposed for the estimation of binary or multinomial choice models to the context of ordered choice models. The estimation approach is based on the existence of a one-to-one mapping from conditional choice value functions to conditional choice probabilities. Exploiting the invertibility of that mapping it is possible to obtain structural parameter estimates without solving the dynamic programming problem.

ESTIMATION OF A DYNAMIC DISCRETE CHOICE MODEL OF IRREVERSIBLE INVESTMENT

In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem.

GMM estimation of a production function with panel data : an application to Spanish manufacturing firms

In this paper we consider the estimation of a Cobb-Douglas production function using a panel dataset of Spanish manufacturing firms. As it is stressed in the econometric literature, the use of standard GMM first differences estimators to eliminate the unobserved firm-specific effects may yield imprecise estimates, particularly in the case of the estimation of the production function. The reason is that the high persistence of output and inputs involved in the estimation of production functions make that their lagged levels to be weak instruments for the first differences of these series. The extended GMM estimator proposed by Arellano and Bover (1995) considers further orthogonality conditions based on lagged differences as instruments for the equation in levels. This approach has been applied to the estimation of technological parameters by Blundell and Bond (1999). Our estimation results, based on this approach, confirm the better performance of the extended GMM estimator compared to the standard first-differenced GMM estimato

GMM ESTIMATION OF A PRODUCTION FUNCTION WITH PANEL DATA: AN APPLICATION TO SPANISH MANUFACTURING FIRMS

In this paper we consider the estimation of a Cobb-Douglas production function using a panel dataset of Spanish manufacturing firms. As it is stressed in the econometric literature, the use of standard GMM first differences estimators to eliminate the unobserved firm-specific effects may yield imprecise estimates, particularly in the case of the estimation of the production function. The reason is that the high persistence of output and inputs involved in the estimation of production functions make that their lagged levels to be weak instruments for the first differences of these series. The extended GMM estimator proposed by Arellano and Bover (1995) considers further orthogonality conditions based on lagged differences as instruments for the equation in levels. This approach has been applied to the estimation of technological parameters by Blundell and Bond (1999). Our estimation results, based on this approach, confirm the better performance of the extended GMM estimator compared to the standard first-differenced GMM estimator

Corporate investment, irreversibilities and lumpiness : an empirical model

We study the role of irreversibility and non convexities in firm investment decisions. For such purpose, we posit a dynamic structural investment model with irreversibility and nonconvex adjustment costs. We focus on the firm decision about whether to invest or not, which is characterized by means of a discrete choice dynamic programming problem. The adjustment cost parameters behind the investment decision are estimated with a longitudinal sample of Spanish manufacturing firms between 1990 and 2002. For these firms, we confirm that inaction and investment episodes account for a significant fraction of them. As estimation procedure, we apply the Nested Pseudo-Likelihood (NPL) algorithm by Aguirregabiria and Mira (2002).We acknowledge research funding from Ministry of Education, Grants No. SEJ2006-05710/ECON and SEJ2006-04957/ECON, respectively. The second author also thanks funding form Comunidad de Madrid, Grant No. CCG07-UAM/HUM-191

Bancos de tempo e creación de capital social: unha análise de datos de transaccións

This article uses transaction data from three time banks located in Barcelona to analyze their otential to generate bonding and bridging social capital for their members. Regarding bonding social capital, the findings are in line with the related literature in terms of the average number of trading partners and the ego-network density. However, reciprocity is a more frequent form of behavior in our data than in other time banks from other countries. Concerning bridging social capital and considering different age groups, the results show slight evidence of homophilic behavior, although intergenerational transactions are also present, being more frequent between more similar age groups. Finally, we explore the influence of age on the time it takes for members to engage in transactions, which could somehow be related to their potential motivations behind joining a time bank.Este artigo utiliza datos de transaccións de tres bancos do tempo situados en Barcelona para analizar o seu potencial para xerar capital social entre os seus membros. En canto aos vínculos do capital social, os resultados están en consonancia coa literatura relacionada en canto ao número medio de socios de intercambio e a densidade da ego-network. Non obstante, a reciprocidade é máis frecuente nos nosos datos que noutros bancos doutros países. En canto á xeración do capital social entre diferentes grupos de individuos e considerando a idade, os resultados mostran lixeiras evidencias de comportamento homofílico, aínda que tamén están presentes transaccións interxeracionais, sendo máis frecuentes entre grupos de idade máis próximos. Finalmente, exploramos a influencia da idade no tempo que tardan os membros en realizar transaccións, o que podería estar relacionado coas súas posibles motivacións detrás de unirse a un banco de tempo.Authors acknowledge financial support from Ministry of Science and Innovation, Grants PID2021-124860NB-I00 (Ángeles Carnero), Grants PID2022-139458NB-I00 and PID2022-138706NB-I00 (Blanca Martinez), Grant PID2022-139614NB-C21 (Rocío Sánchez Mangas); and from Generalitat Valenciana, Grant CIPROM/2021/060 (Ángeles Carnero)

An empirical assessment of the impact of public research contracts on scientific productivity

We study the e§ect of a Program, aimed at Önancing high qual- ity researchers to integrate them into the Spanish scientiÖc system, on the relative ex post performance of the researchers awarded. We assess the e§ect of the contract status on the scientiÖc productivity of applicants, in the four-year period after application. Both the con- ditional regression and the matching results show that the contract status has no e§ect on the average number of published contributions, but it exhibits, for several areas, a positive e§ect on the scientiÖc qual- ity of contributions (as measured by its impact). This result points out the success of the Program in increasing the scientiÖc impact of the Spanish system