Semiparametric Estimation of Single-Index Transition Intensities

This research develops semiparametric kernel-based estimators of state-specific conditional transition intensitiesm, hs (y|x), for duration models with right-censoring and/or multiple destinations (competing risks). Both discrete and continous duration data are considered. The maintained assumptions are that hs(y|x) depends on x only through an index x'Bs. In contrast to existing semiparametric estimators, proportional intensities is not assumed. The new estimators are asymptotically normally distributed. The estimator of Bs is root-n consistent. The estimator of hs (y|x) achieves the one-dimensional rate of convergence. Thus the single-index assumption eliminates the "curse of dimensionality". The estimators perform well in Monte Carlo experiments.semiparametric estimation; kernel regression; duration analysis; competing risks; censoring

Testing a Parametric Function Against a Nonparametric Alternative in IV and GMM Settings

This paper develops a specification test for functional form for models identified by moment restrictions, including IV and GMM settings. The general framework is one where the moment restrictions are specified as functions of data, a finite-dimensional parameter vector, and a nonparametric real function (an infinite-dimensional parameter vector). The null hypothesis is that the real function is parametric. The test is relatively easy to implement and its asymptotic distribution is known. The test performs well in simulation experiments.Generalized method of moments, specification test, nonparametric alternative, LM statistic, generalized arc-sine distribution

Growth, Income and Regulation: a Non-Linear Approach

This paper analyzes the effect on GDP growth of income (GDP per capita) and economic regulation. A simple theoretical framework presents two opposing views. We analyze the empirical relation using a non-linear dynamic panel data model with fixed effects. The result shows that the effect of regulation on growth depends on income. For low-income countries, there is little effect of changing regulation. For highly regulated middle-income countries, deregulation can increase growth. For high-income countries, deregulation leads to higher growth. Holding regulation constant, there is catch-up growth with a maximum at an intermediate income level.catch-up growth; economic freedom; fixed effects; GMM; specification tests

A Duration Analysis of the Time Taken to Find the First Job for Newly Arrived Migrants in Australia

This paper extends the traditional static focus of research on the labour market assimilation of migrants in Australia by analyzing the dynamics of job search and actual time taken to find the first job after arrival in Australia. The Longitudinal Survey of Immigrants to Australia (LSIA) covers two cohorts of recent migrants to Australia that differ considerably in immigration selection criteria and other policy settings, as well as in the macroeconomic employment conditions at their time of arrival in Australia. This gives rise to very different early labour market outcomes for the migrants in these two cohorts; and this paper looks at one specific aspect of this differing outcome – the time taken to find the first job after arrival in Australia. ¶ We analyze the inter-cohort differences in migrant characteristics and job search behaviour, and explicitly model the duration of the time taken to find the first job in Australia for the sub-sample of migrants who were the Principal Applicants in their visa applications. Using a conventional proportional hazards model framework, estimation results are presented for a Cox model specification and for a parameterized version of the baseline hazard which permits a formal test of equivalent hazards faced by the migrants in the two cohorts of LSIA. ¶ We find that the hazard rates of time to first job are determined by pre-immigrant characteristics, such as education and qualifications, recent work history in source country, the Australian visa categories, English language proficiency, and whether the migrants had previously visited Australia. The parametric model results show that both the underlying baseline hazards and the proportional hazard coefficients on most variables of interest differ significantly between Cohort 1 (arrived in Australia in 1993 through 1995) and Cohort 2 (arrived in Australia in 1999-2000). ¶ We then use the parametric model results to simulate the full distribution of the time taken to find the first job for these two migrant cohorts. We present alternative decompositions of the inter-cohort gap into effects due to differences in the observable characteristics of the migrants, and residual effects which can be attributed to different selection criteria and other policy settings and macro economic conditions that are applicable for the two time periods. ¶ The decomposition results suggest that the more favourable outcomes for Cohort 2 migrants are predominantly due to the setting of the Cohort 2 time period. This effect is most pronounced for the sample of female Principal Applicants. Cohort 1 migrants would also have experienced much quicker exits to a first job had they arrived under the macroeconomic and immigration policy setting of Cohort 2. Although the advantage derived from the Cohort 2 setting is not itself further decomposed, our analyses does indicated an important role for changes in migrating selection criteria to affect initial labour market outcomes of migrants after arrival in Australia

Semiparametric Estimation of Single-Index Transition Intensities

This research develops semiparametric kernel-based estimators of statespecific conditional transition intensities, hs(y|x), for duration models with right-censoring and/or multiple destinations (competing risks). Both discrete and continuous duration data are considered. The maintained assumptions is that hs(y|x) depends on x only through an index x ′ βs. In contrast to existing semiparametric estimators, proportional intensities is not assumed. The new estimators are asymptotically normally distributed. The estimator of βs is root-n consistent. The estimator of hs(y|x) achieves the one-dimensional rate of convergence. Thus the single-index assumption eliminates the “curse of dimensionality”. The estimators perform well in Monte Carlo experiments

Nonparametric comparison of regression curves by local linear fitting

This paper proposes a new nonparametric test for the hypothesis that the regression functions in two or more populations are the same. The test is based on local linear estimates using data-driven bandwidth selectors. The test is applicable to data with random regressors and heteroskedastic responses. Simulations indicate the test has good power.Nonparametric testing Local polynomial fitting Bias correction