A logistic regression point of view toward loss given default distribution estimation

We propose a new procedure to estimate the loss given default (LGD) distribution. Owing to the complicated shape of the LGD distribution, using a smooth density function as a driver to estimate it may result in a decline in model fit. To overcome this problem, we first apply the logistic regression to estimate the LGD cumulative distribution function. Then, we convert the result into the LGD distribution estimate. To implement the newly proposed estimation procedure, we collect a sample of 5269 defaulted debts from Moody’s Default and Recovery Database. A performance study is performed using 2000 pairs of in-sample and out-of-sample data-sets with different sizes that are randomly selected from the entire sample. Our results show that the newly proposed procedure has better and more robust performance than its alternatives, in the sense of yielding more accurate in-sample and out-of-sample LGD distribution estimates. Thus, it is useful for studying the LGD distribution.     

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.     

The impact of privatization on efficiency and profitability

Over the past three decades, China has undergone tremendous economic and social change as a consequence of the transition from a centrally planned to a market economy. This paper examines a key feature of this transition – the privatization of the state‐owned enterprises (SOEs) – through both a theoretical model and empirical analysis. Using newly collected primary data from a variety of sources, we study how privatization of listed SOEs affects employment, wages, profits and other aspects of economic performance at the firm level. Our major finding is that privatization results in substantial downsizing of employment, increased labour productivity and rising profitability.     

The effect of heterogeneous beliefs on mergers and acquisitions

This article investigates the effect of heterogeneous beliefs on firms’ mergers and acquisitions (M&A) decisions. Using data of China’s financial market, which is featured with great heterogeneity of belief, we find that heterogeneous beliefs are positively associated with the occurrence of M&A transactions, and firms with greater heterogeneous beliefs are more likely to pay the transactions with stock. Moreover, we show that government intervention, measured by state ownership, weakens the effect of heterogeneous beliefs on firms’ M&A decisions.     

How middle managers manage the political environment to achieve market goals: Insights from China's state‐owned enterprises

Research summary: Although the middle management literature has identified various bridging roles performed by middle managers in the market environment, it is relatively vague about whether and how they manage the political environment to achieve market‐related goals. In an inductive field study of four large state‐owned enterprises based in mainland Communist China, operational middle managers were found to take an active role in dealing with political actors to achieve market efficiency in their local environments, performing two distinct bridging strategies. Our field study suggests that middle managers are better equipped than their bosses (top executives) as well as their subordinates (frontline employees) to perform the bridging function between competing market and political imperatives in various local settings. Managerial summary: For firms that operate in diverse geographies, it is challenging for a handful of top executives to deal with numerous political actors. This burden could be shared with operational middle managers, who play a bridging role by drawing on their operational knowledge and local networks. Our research on middle managers who work under the scrutiny of political actors in China found that they bridge market and political ideology by conveying common features that seem legitimate to both. They also bridge market goals and political actors with personal affect. Compared to top executives and frontline employees, middle managers have unique advantages in performing these bridging functions. Firms can enhance their strategy execution ability by training middle managers in dealing with political actors in diverse contexts. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

国库最佳库底现金测算方法研究

随着国库集中收付管理制度改革的不断深入，我国国库库存现金余额呈现出快速增长的趋势。通过对确定最佳库底现金的主要模型进行介绍，以国家金库重庆市分库为对象进行了实证分析。以期为实际工作和相关研究提供一定参考。     

State‐contingent analysis of farmers’ response to weather variability: irrigated dairy farming in the Murray Valley,Australia

The agricultural sector is commonly regarded as one of the most vulnerable to climate change. Current understanding of the impact of climate change on this sector relies on the underlying assumptions about farmers’ possible responses to weather variability, including changes in crop choice, input combinations and land management practices. Many previous analyses rely on the implicit (and restrictive) assumption that farmers operate under a fixed technology set across different states of nature. This assumption, represented through stochastic production or profit functions, is commonly made but seldom tested and may understate farmers’ responses to climate change if state‐contingent production technologies are, in reality, more flexible. The potential for farmers to adapt production technologies in response to unforeseen events is at the core of the state‐contingent approach. Advanced in Chambers and Quiggin (2000), the theory contends that producers can manage uncertainty through the allocation of productive inputs to different states of nature. In this article, we test the assumption that farmers’ observed behaviour is consistent with the state‐contingent production theory using farm‐level data from Australia. More precisely, we estimate the milk production technology for a sample of irrigated dairy farms from the southern Murray–Darling Basin over the period from 2006–2007 to 2009–2010.