WOMEN PREFER LARGER GOVERNMENTS: GROWTH,STRUCTURAL TRANSFORMATION,AND GOVERNMENT SIZE

The increase in income per capita is accompanied, in virtually all countries, by two changes in economic structure: the increase in the share of government spending in gross domestic product (GDP), and the increase in female labor force participation. We argue that these two changes are causally related. We develop a growth model based on Galor and Weil (1996) where female participation in market activities, fertility, and government size, in addition to consumption and saving, is endogenously determined. Rising incomes lead to a rise in female labor force participation as the opportunity cost of staying at home and caring for the children increases. In our model, higher government spending decreases the cost of performing household chores, including, but not limited to, child rearing and child care, as in Rosen (1996) . We also use a wide cross‐section of data for developed and developing countries and show that higher market participation by women is positively and robustly associated with government size. We then investigate the causal link between participation and government size using a novel unique data set that allows the use of the relative price of productive home appliances as an instrumental variable. We find strong evidence of a causal link between female market participation and government size. This effect is robust to the country sample, time period, and a set of controls in the spirit of Rodrik (1998) . (JEL O4, E62, H11)     

Model-based Clustering of Sequential Data with an Application to Contraceptive Use Dynamics

ABSTRACT

Multi-state models describe the transitions people experience as life unfolds. The transition probabilities depend on sex, age, and attributes of the person and the context. Empirical evidence suggests that attributes that cannot be measured directly may at most be inferred from a long list of observable characteristics. A cluster-based, discrete-time multi-state model is presented, where transition probabilities are estimated simultaneously for several subpopulations of a heterogeneous population. The subpopulations are not defined a priori but are determined on the basis of similarities in behavior in order to determine which women exhibit similar characteristics with respect to method choice, method switch, discontinuation and subsequent resumption of contraceptive use. The data are from the life history calendar based on the Brazilian Demographic and Health Survey 1996. The parameters of the model are estimated using the EM algorithm. Seven subpopulations with heterogeneous transition probabilities are identified.     

Central Limit Theorems for the Non‐Parametric Estimation of Time‐Changed Lévy Models

Abstract. Let {Z_t}_{t 0} be a Lévy process with Lévy measure ν and let be a random clock, where g is a non‐negative function and is an ergodic diffusion independent of Z. Time‐changed Lévy models of the form are known to incorporate several important stylized features of asset prices, such as leptokurtic distributions and volatility clustering. In this article, we prove central limit theorems for a type of estimators of the integral parameter β(?):=∫?(x)ν(dx), valid when both the sampling frequency and the observation time‐horizon of the process get larger. Our results combine the long‐run ergodic properties of the diffusion process with the short‐term ergodic properties of the Lévy process Z via central limit theorems for martingale differences. The performance of the estimators are illustrated numerically for Normal Inverse Gaussian process Z and a Cox–Ingersoll–Ross process .     

An Age-Structured Model for Childhood Obesity

An age-structured model for childhood obesity at population level is fitted to empirical data in order to predict the proportion of overweighted and obese children in the 6–8 and 9–12 year old classes in the region of Valencia, Spain.     

A heterarchical generic discrete manufacturing simulation model and its application in a world class manufacturing environment

Current factory design and evaluation is very primitive. Factory components are designed in many cases independently. Product and process design are not well integrated. An encompassing framework is needed for iterating through a series of total factory designs, searching for optimal performance. In addition, a vehicle is needed for predicting the performance of a proposed advanced manufacturing system, so that engineers may have a sound means for evaluating such proposals. A heterarchical discrete manufacturing SIMNET II simulation model (SIMCELLS) was developed as a comprehensive methodology for designing and evaluating discrete manufacturing systems. SIMCELLS allows manufacturing systems engineers to experiment with alternative system structures and control strategies while seeking that combination of design features that will produce the desired overall system performance. The model in combination with a modernization programme is enabling a firm to successfully manufacture and sell trucks meeting international standards. The SIMNET II model