Properties of Census Dual System Population Size Estimators

We study parametric and non‐parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post‐stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model‐based approaches are generally biased unless the model is correctly specified. We then study a local post‐stratification approach based on a non‐parametric kernel estimate of the Census enumeration functions. We illustrate that the non‐parametric approach avoids the risk of model mis‐specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post‐enumeration survey data.     

浅谈水利水电工程概预算的编制与应用

本文详细介绍了水利水电工程概预算编制依据、步骤、注意事项,探讨了水利水电工程概预算编制过程中常见问题的分析处理。     

The determinants of commercial banking profitability in low-, middle-, and high-income countries

Using a broad bank-level dataset and the GMM estimator technique described by Arellano and Bover (1995), this paper analyses how bank-specific characteristics, macroeconomic variables, and industry-specific factors affect the profitability of 10,165 commercial banks across 118 countries over the period from 1998 to 2012. Grouping the countries according to three income levels, we show that the determinants of bank profitability included in our model can explain existing profitability differences among commercial banks in low-, middle-, and high-income countries. The profitability determinants vary quite widely across the different levels of income in terms of significance, sign and size of the effect. The level of income has thus an important impact on the determinants of bank profitability.     

Does the labor-income process contain a unit root? Evidence from individual-specific time series

Calibrations of models related to life-cycle behavior of consumption and saving often invoke the important assumption of a unit root in individuals׳ labor-income process. We for the first time test this assumption using methods for univariate time series. Based on longitudinal register data from 1968 to 2005, we first estimate an autoregressive model for each individual using a method for approximately median-unbiased estimation. We then exploit the resulting distribution of the individual-specific estimates to draw inference about the presence of a unit root. Results indicate that earnings for the representative worker are governed by a process where shocks to earnings have moderate persistence and are both economically and statistically significantly different from having permanent effects. These results question the heavy use of unit-root processes for earnings.     

Shrinkage estimation of semiparametric multiplicative error models

Within models for nonnegative time series, it is common to encounter deterministic components (trends, seasonalities) which can be specified in a flexible form. This work proposes the use of shrinkage type estimation for the parameters of such components. The amount of smoothing to be imposed on the estimates can be chosen using different methodologies: Cross-Validation for dependent data or the recently proposed Focused Information Criterion. We illustrate such a methodology using a semiparametric autoregressive conditional duration model that decomposes the conditional expectations of durations into their dynamic (parametric) and diurnal (flexible) components. We use a shrinkage estimator that jointly estimates the parameters of the two components and controls the smoothness of the estimated flexible component. The results show that, from the forecasting perspective, an appropriate shrinkage strategy can significantly improve on the baseline maximum likelihood estimation.     

Estimating structural equation models with non-normal variables by using transformations

We discuss structural equation models for non-normal variables. In this situation the maximum likelihood and the generalized least-squares estimates of the model parameters can give incorrect estimates of the standard errors and the associated goodness-of-fit chi-squared statistics. If the sample size is not large, for instance smaller than about 1000, asymptotic distribution-free estimation methods are also not applicable. This paper assumes that the observed variables are transformed to normally distributed variables. The non-normally distributed variables are transformed with a Box–Cox function. Estimation of the model parameters and the transformation parameters is done by the maximum likelihood method. Furthermore, the test statistics (i.e. standard deviations) of these parameters are derived. This makes it possible to show the importance of the transformations. Finally, an empirical example is presented.     

Consistent estimation of a general nonparametric regression function in time series

We propose an estimator of the conditional distribution of X_t|X_t−1,X_t−2,…, and the corresponding regression function , where the conditioning set is of infinite order. We establish consistency of our estimator under stationarity and ergodicity conditions plus a mild smoothness condition.     

Decomposing productivity patterns in a conditional convergence framework

In this study we examine regional data on per worker GDP, disaggregated at sectoral level, by focusing our interest on the role of differences in the sectoral composition of activities, and in productivity gaps that are uniform across sectors, in explaining the catching-up process, which is realized through physical and human capital as well as technological knowledge accumulation. Our objective is to investigate how much of the interregional inequality in aggregate productivity per worker is imputable to each component. A methodology for identifying and analyzing sources of inequality from a decomposed perspective is developed in the growth framework by combining a shift-share based technique and a SUR model specification for the conditional-convergence analysis. The proposed approach is employed to analyze aggregate interregional inequality of per worker productivity levels in Italy over the period 1970–2000. With respect to the existing empirical results, our approach provides a more comprehensive and detailed examination of the contribution of each identified component in explaining the regional productivity gaps in Italy. It is argued that region-specific productivity differentials, uniform across sectors, explain a quite large share of differences in productivity per worker. However, sectoral composition plays a non negligible role, although decreasing since the end of 1980s, and very different productivity patterns emerge within geographical areas.

How do trade openness,public expenditure and institutional performance affect unemployment in OIC countries? Evidence from the DCCE approach

This study explores the relationship between trade openness, public expenditure, institutional performance, and unemployment in member countries of the Organization of Islamic Cooperation (OIC) (formerly the Organization of the Islamic Conference). The conventional panel data techniques overlook cross-sectional dependence and yield-biased results. A new methodology called dynamic common correlated effects (DCCE) is employed to deal with the issue of cross-sectional dependence. The long-run results demonstrate that trade openness is inversely and significantly associated with overall unemployment and youth unemployment in lower-income as well as all the OIC economies and positively correlated in the higher-income OIC group. Public expenditure has an inverse and significant correlation with unemployment in OIC countries overall and higher-income OIC countries. Moreover, institutional performance and foreign direct investment are negatively related to unemployment in all OIC economies. The research shows the need for the continuation of open trade policies, strong institutions, and higher public expenditure in the OIC countries in order to decrease overall unemployment—in particular, youth unemployment.