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on Econometrics |
| By: | Anthony Murphy (Nuffield College, Oxford) |
| Abstract: | A relatively simple and convenient score test of normality in the bivariate probit model is derived. Monte Carlo simulations show that the small sample performance of the bootstrapped test is quite good. The test may be readily extended to testing normality in related models. |
| Keywords: | Score test, bivariate probit, normality, Gram-Charlier series |
| JEL: | C25 |
| Date: | 2005–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0512004&r=ecm |
| By: | Mogens Fosgerau (Danish Transport Research Institute); Michel Bierlaire (Ecole Polytechnique Fédérale de Lausanne) |
| Abstract: | The choice of a specific distribution for random parameters of a discrete choice model is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious biases in model forecast and in the estimated means of random parameters. In this paper we propose a practical test, based on seminonparametric techniques. The test is analyzed both on synthetic and real data, and is shown to be simple and powerful. |
| Keywords: | Seminonparametric, discrete choice, mixed logit, value of time |
| JEL: | C1 C2 C3 C4 C5 C8 |
| Date: | 2005–12–05 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0512002&r=ecm |
| By: | Andrea, SILVESTRINI |
| Abstract: | In this paper we feature state-of-the-art econometric methodology of temporal aggregation for univariate linear time series, namely ARIMA-GARCH models. We present a unified overview of temporal aggregation techniques for this broad class of processes and we explain in detail, although intuitively, the technical machinery behind the results. An empirical application with Belgian public deficit data illustrates the main issues. |
| Keywords: | Temporal aggregation; ARIMA, GARCH, seasonality |
| JEL: | C10 C22 C43 |
| Date: | 2005–08–15 |
| URL: | http://d.repec.org/n?u=RePEc:ctl:louvec:2005044&r=ecm |
| By: | Mehmet Caner (University of Pittsburgh) |
| JEL: | C1 C2 C3 C4 C5 C8 |
| Date: | 2005–12–09 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0512009&r=ecm |
| By: | Gad Allon (Northwestern University); Michael Beenstock (Hebrew University); Steven Hackman (Georgia Tech); Ury Passy (Technion); Alex Shapiro (Georgia Tech) |
| Abstract: | An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions. |
| Keywords: | convex programming, production functions, entropy |
| JEL: | C1 C2 C3 C4 C5 C8 |
| Date: | 2005–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0512003&r=ecm |
| By: | Francisca Antman (Stanford University); David J. Mckenzie (The World Bank) |
| Abstract: | The degree of mobility in incomes is often seen as an important measure of the equality of opportunity in a society and of the flexibility and freedom of its labor market. But estimation of mobility using panel data is biased by the presence of measurement error and non-random attrition from the panel. This paper shows that dynamic pseudo-panel methods can be used to consistently estimate measures of absolute and conditional mobility in the presence of non-classical measurement errors. These methods are applied to data on earnings from a Mexican quarterly rotating panel. Absolute mobility in earnings is found to be very low in Mexico, suggesting that the high level of inequality found in the cross-section will persist over time. However, the paper finds conditional mobility to be high, so that households are able to recover quickly from earnings shocks. These findings suggest a role for policies which address underlying inequalities in earnings opportunities. |
| Keywords: | Poverty, Labor and employment |
| Date: | 2005–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:3745&r=ecm |
| By: | Frédérick Demers |
| Abstract: | The author proposes and evaluates econometric models that try to explain and forecast real quarterly housing expenditures in Canada. Structural and leading-indicator models of the Canadian housing sector are described. The long-run relationship between expenditure and its determinants is shown to have shifted during the late 1970s, which implies that important changes have occurred in how the housing market is driven. The author finds that the response of housing investment to interest rates has become more pronounced over time. He compares out-of-sample forecasts from linear and non-linear cointegration models (which make use of information on fundamentals such as wealth and demographics) with forecasts from simple leading-indicator models (which exploit information such as housing starts or household indebtedness). The author finds that simple leading-indicator models can provide relatively accurate near-term forecasts. The preferred structural model, which allows for a shift in the cointegrating vector, provides a rich analysis of the housing sector, with good forecast accuracy on the construction side but not on the resale side, which is more difficult to predict. |
| Keywords: | Economic models; Econometric and statistical methods |
| JEL: | R21 E27 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:05-41&r=ecm |
| By: | Anton Korinek (The World Bank); Johan A. Mistiaen (The World Bank); Martin Ravallion (The World Bank) |
| Abstract: | Past approaches to correcting for unit nonresponse in sample surveys by re-weighting the data assume that the problem is ignorable within arbitrary subgroups of the population. Theory and evidence suggest that this assumption is unlikely to hold, and that household characteristics such as income systematically affect survey compliance. The authors show that this leaves a bias in the re-weighted data and they propose a method of correcting for this bias. The geographic structure of nonresponse rates allows them to identify a micro compliance function, which they then use to re-weight the unit-record data. An example is given for the U.S. Current Population Surveys, 1998-2004. The authors find, and correct for, a strong household income effect on response probabilities. |
| Keywords: | Poverty |
| Date: | 2005–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:3711&r=ecm |