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.     

Economics and underdetermination: a case study of urban land and housing economics

Underdetermination, associated with the Duhem–Quine thesis,is a familiar if under-researched theme in economics. In thelight of this, we examine the development of urban land andhousing economics. Through its Cartesian dualistic delineationof theory and data, the contemporary mainstream approach appearsunable to circumvent the problem of underdetermination. In effect,it employs the strong version of Duhem–Quine in its retentionof the assumption of a single, unitary competitive market (andassociated access–space trade-off). Conversely, we highlightthe affinity of Ely's (and the later Columbia School's) approachto pragmatists Dewey and Peirce, which provides a more fruitfulbasis for explanation.     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ

Bayesian multiple imputation (MI) has become a highly useful paradigm for handling missing values in many settings. In this paper, I compare Bayesian MI with other methods – maximum likelihood, in particular—and point out some of its unique features. One key aspect of MI, the separation of the imputation phase from the analysis phase, can be advantageous in settings where the models underlying the two phases do not agree.     

Measurement error and panel data1

The underidentification of linear models with measurement error does not necessarily extend to panel data models, as has been shown by GAiliches and Hausman (1986). We discuss and extend some of their results for a simple case and address particular issues concerning identification and asymptotic variances.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

Costs of financial instability, household-sector balance sheets and consumption

Extant work on costs of financial instability focuses on fiscal costs and declines in aggregate GDP following banking crises. We estimate effects of banking and currency crises on consumption in 19 OECD countries, showing consumption plays an important role in the adjustment following a crisis, and effects are not captured solely by the impact of crises on standard consumption determinants, income and wealth. Additional effects, attributable to factors such as time-varying confidence, uncertainty and credit rationing, are aggravated by high and rising leverage, despite financial liberalisation easing liquidity constraints. High leverage implies that banking crises taking place now could have greater incidence than in the past.     

中国进口与经济增长关系的区域差异分析

利用面板数据对中国东、中、西部的进口额和GDP增长关系进行的实证研究。在短期内，GDP增长对进口额影响最小是中部地区，在长期，西部GDP增长对进口额影响最大。中国经济增长对拉动世界经济增长起了十分重要的作用，中国经济增长减速也会影响全球经济。     

RESEARCH NOTE: ERRORS IN THE OCTOBER HOUSEHOLD SURVEY 1994 AVAILABLE FROM THE SOUTH AFRICAN DATA ARCHIVE1

The on‐line electronic documentation supplied with the 1994 October Household Survey by the South African Data Archive (SADA) appears to be incorrect. In particular, the electronic version of the questionnaire does not correspond to the hard copy in the possession of the author. The most serious error is that the race classification in the electronic copy is different from the classification on the hard copy. Researchers relying on the electronic copy will erroneously interchange the categories “Coloured”, “White” and “Black”. This could lead to seriously misleading analyses. The reason for this mistake can probably be attributed to a retyping of the questionnaire using the 1993 OHS as a template.