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.     

The moments of the Gompertz distribution and maximum likelihood estimation of its parameters

The Gompertz distribution is widely used to describe the distribution of adult deaths. Previous works concentrated on formulating approximate relationships to characterise it. However, using the generalised integro-exponential function, exact formulas can be derived for its moment-generating function and central moments. Based on the exact central moments, higher accuracy approximations can be defined for them. In demographic or actuarial applications, maximum likelihood estimation is often used to determine the parameters of the Gompertz distribution. By solving the maximum likelihood estimates analytically, the dimension of the optimisation problem can be reduced to one both in the case of discrete and continuous data. Monte Carlo experiments show that by ML estimation, higher accuracy estimates can be acquired than by the method of moments.     

Economic contribution of essential air service flights on small and remote communities

The Essential Air Service Program (EAS) has attracted considerable criticism and has been a target for either modification or complete termination almost since its inception through the Airline Deregulation Act in 1978. Although its opponents emphasize the program's inefficiency, its supporters claim that the program is crucial to accessing small and remote communities, which helps them develop economically and socially. This paper demonstrates the economic contributions of EAS flights to small and remote communities. Using a two-stage least squares estimation, the major findings indicate that a 1% increase in air passenger traffic in EAS airports with a minimum annual air passenger traffic of 1000 likely leads to a 0.12% increase in per capita income of the community served by that airport. Our results also suggest that EAS communities that are able to sustain their subsidized flights experienced higher per capita income growth in the 1999–2011 period than did ex-EAS communities that lost their flights as a result of non-eligibility.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

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.     

Public sector enterprise disinvestment in India: Efficiency gains in a political context

India instituted a program of state enterprise disinvestment in 1991 as part of a sweeping reform initiative. This study analyses the effect of disinvestment on enterprise performance, conditioned on political context as characterized by the ideological leanings of the parties in power at state and central levels. Using stochastic frontier analysis, measures of firm efficiency are generated for 238 central public sector enterprises for the period 1991–1992 to 2010–2011. The relationship between efficiency so measured and disinvestment is then estimated using a two-stage instrumental variables approach to control for endogeneity between firm efficiency and selection for disinvestment. Initial disinvestment is associated with substantial efficiency gains, but subsequent disinvestment much less so and the proportion of shares disinvested only loosely so. This may be explained by the transformative effect of initial stock market listing on accountability and profit orientation that is not repeated with further rounds of disinvestment. The effect of disinvestment on performance is stronger if the enterprise is located in a state governed by a right leaning party or one that is ideologically aligned with the party in power at the centre.     

The expected real yield and inflation components of the nominal yield curve

The term structure of real yields and expected inflation are two unobserved components of the nominal yield curve. The primary objectives of this study are to decompose nominal yields into their expected real yield and inflation components and to examine their behaviour using state-space and regime-switching frameworks. The dynamic yield-curve models capture three well-known latent factors – level, slope, and curvature – that accurately aggregate the information for the nominal yields and the expected real and inflation components for all maturities. The nominal yield curve is found to increase slightly with a slope of about 120 basis points, while the real yield curve slopes upward by about 20 basis points, and the expected inflation curve is virtually flat at slightly above 2 per cent. The regime-switching estimations reveal that the nominal yield, real yield and expected inflation curves have shifted down significantly since 1999.     

Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

Some Variants of Constrained Estimation in Finite Population Sampling

This is a review article that unifies several important examples using constrained optimisation techniques. The basic tools are three simple mathematical optimisation results subject to certain constraints. Applications include calibration, benchmarking in small area estimation and imputation. A final illustration is constrained optimisation under a general divergence loss.     

重叠滤波多音系统的频偏性能分析及优化

重叠滤波多音(O-FMT)是针对滤波多音(FMT)系统频谱利用率低的缺点而根据超奈奎斯特(FTN)概念引入子载波重叠得到的方案。鉴于O-FMT系统在频偏环境下的性能缺陷，理论分析了频偏对系统信号各部分的影响，比较了O-FMT与正交频分复用（OFDM）系统的抗频偏性能。针对频偏性能优化问题，提出了基于最佳线性无偏估计（BLUE）的改进盲估计算法，设计了基于频域滤波器系数的内嵌结构进行频偏补偿。仿真实验表明，O-FMT相比OFDM具有更好的抗频偏能力，改进的盲估计算法估计值精度更高，抗干扰、抗衰落能力更强，设计的频偏补偿结构可以使系统获得更好的性能。