LABOUR SUPPLY ESTIMATION AND PUBLIC POLICY

Abstract. Economists devote considerable energies towards refining their econometric techniques to overcome difficulties connected with conducting empirical research. Despite advances in technique. it is not clear whether further refinement in this direction is worthwhile for policy purposes. It may be that no further amount of statistical adjustment of inadequate data will increase understanding, and that better data is simply necessary to add to our knowledge. But rarely is sufficient credit paid to new forms of data. In short, econometric technique is emphasized to the neglect of data innovation, as if new data were merely lying about waiting for an ingenious suggestion for use. This paper surveys advances of the last twenty five years in estimating labour supply for policy purposes with a view towards appreciating the relative contribution of both improvements in econometric technique as well as developments of new data.
After briefly detailing the key parameters which economists have sought to estimate, we describe the early 'first generation' research (circa 1970), which is plagued by problems of unobservable variables, measurement errors, truncation and selectivity bias, and non linear budget constraints. 'Second generation' research constitute attempts to resolve one or more of these difficulties, and the respective contribution of econometric technique and new data is acknowledged and assessed, including the contribution of data generated by large scale social experiments in which participants are randomly assigned to different guaranteed income plans and their labour supply behaviour measured.     

The Robustness of the APT to Alternative Estimators

We test the robustness of the APT to two alternative estimation procedures: the Fama and MacBeth (1973) two-step methodology; and the one-step procedure due to Burmeister and McElroy (1988). We find that the APT is indeed sensitive to the chosen estimator and assumptions about the factor structure of stock returns. We believe that our findings have implications for the estimation of asset pricing models in general.     

复杂性管理策略:关注整体性

复杂性管理的策略首先要关注和认识复杂系统的整体性,这要通过关注系统的结构、多元化的视角、容忍模糊性和不确定性、借助直觉等手段来达到。在关注和认识整体性的基础上,需要进一步维护和促进复杂系统的整体性,这需要通过保护系统的自组织、创造自组织环境条件、发现和维护序参量、鼓励多元化以及与环境相协调来达成。     

Services inflation dynamics and persistence puzzle in Brazil: a time-varying parameter approach

This article analyses services inflation dynamics in Brazil, focusing on the Services Inflation Persistence Puzzle, for monthly data from January 2004 to February 2016. We apply a time-varying parameter (TVP) approach, via a Kalman filter, to estimate hybrid Phillips curves and compare inflation inertia for tradable goods and services inflation. Aggregate Brazilian Extended Consumer Price Index inflation serves as a benchmark. To justify the TVP analysis, parameter instability and structural change tests are implemented, based on OLS and Generalized Method of Moments (GMM) frameworks. The main results are as follows: (i) the TVP approach is relevant due to observed instability in some parameters estimated; (ii) inflation expectation coefficients are higher than lagged inflation in all calculations, but inflation inertia is not negligible at all; (iii) services inflation persistence ranges from 27 to 36%, whereas tradable goods inflation persistence ranges from 36 to 47%, providing evidence of the Services Inflation Persistence Puzzle in Brazil; (iv) from 2009 onwards an increase in one percentage point in real wages raises monthly services inflation rate by 0.02 to 0.03 percentage point; (v) there is evidence that cost-push pressures, due to wage increases in the service sector, are more important to explain services inflation than demand pressures from early 2009 to mid-2014.     

对《包法利夫人》的译本翻译批评研究

文学文本可视为一个有若干“义”与“意”组成的集合体,可分为概念逻辑意义、内涵意义、情感意义、搭配意义、文化意义、美学修辞意义、语法意义、语用意义、风格意义等。该文在此系统意义参数的理论基础上,对文学作品《包法利夫人》的译作进行了翻译评析。     

宽松的环境政策能吸引更多的外商直接投资吗——基于中国工业省级面板数据的分析

利用我国1997~2009年的工业省级面板数据和动态面板GMM估计方法,考察了相对宽松的环境政策是否是吸引FDI的主要原因。研究发现,环境政策较宽松的地区能够吸引更多的外资流入,但这种影响并不大,所以,以降低环境标准、牺牲环境为代价来吸引FDI不是明智之举;与东、中部地区相比,西部在吸引FDI上处于明显劣势,这在一定程度上加剧了我国经济结构的失衡。     

Monetary policy matters: Evidence from new shocks data

The evidence suggests that monetary policy post 1988 became more forward-looking, invalidating the identifying assumptions in conventional methods of measuring monetary policy's effects, leading to spurious and unlikely results for this period. We propose a new identification scheme that uses factors extracted from Fed Funds futures to measure exogenous changes in policy. Using this shock series in a VAR, we recover the contractionary effect of monetary tightening on output. Moreover, we find that as much as half of the variability in output was driven by monetary policy shocks, and that there is a mild price puzzle.     

An improved bootstrap test of stochastic dominance

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null hypothesis under regularity conditions. This paper also characterizes the set of probabilities so that the asymptotic size is exactly equal to the nominal level uniformly. As our simulation results show, these characteristics of our tests lead to an improved power property in general. The improvement stems from the design of the bootstrap test whose limiting behavior mimics the discontinuity of the original test’s limiting distribution.     

汽车工业供应物流要货参数模型研究

结合汽车工业供应物流的实际情况,将正常供货的服务能力及成本、应急供货服务能力及成本、缺货损失成本及不同供货事件的概率引入到供应物流总成本模型当中,充分揭示了供应物流日常运作决策中所要权衡的核心矛盾,反映了汽车供应物流运作的战略支持价值。在这个基础上,导出要货参数模型,如最佳供货间隔周期模型、最佳供货批量模型。针对影响最佳供货批量的主要因素进行了灵敏度分析,找到了供应物流优化的重点。     

Functional-coefficient models for nonstationary time series data

This paper studies functional coefficient regression models with nonstationary time series data, allowing also for stationary covariates. A local linear fitting scheme is developed to estimate the coefficient functions. The asymptotic distributions of the estimators are obtained, showing different convergence rates for the stationary and nonstationary covariates. A two-stage approach is proposed to achieve estimation optimality in the sense of minimizing the asymptotic mean squared error. When the coefficient function is a function of a nonstationary variable, the new findings are that the asymptotic bias of its nonparametric estimator is the same as the stationary covariate case but convergence rate differs, and further, the asymptotic distribution is a mixed normal, associated with the local time of a standard Brownian motion. The asymptotic behavior at boundaries is also investigated.