Using Quality of Interview Information to Assess Nonrandom Attrition Bias in Developing-Country Panel Data

Panel data often provide an understanding of household behavior not possible with cross‐sectional information alone. However, a disturbing feature of such data is that there can be substantial, nonrandom attrition and many analysts share the concern that this inhibits the ability to make accurate inferences. The author examines attrition in the KwaZulu–Natal Income Dynamics Study 1993–1998, assesses the extent of attrition bias for a specific empirical example, and proposes and implements a selection correction methodology using quality of first round interview variables as identifying instruments. The results show that attrition does lead to statistical bias in the “behavioral” coefficients in estimation of household‐level expenditure functions. Since it is typically difficult to determine the bias for a particular analysis a priori, and such bias is by its nature model‐specific, it behooves researchers using panel data to evaluate the effects of attrition in their analyses.     

Complex ballot propositions,individual voting behavior,and status quo bias

One concern about direct democracy is that citizens may not be sufficiently competent to decide about complex policies. This may lead to exaggerated conservatism in the voting decision (status quo bias). To investigate how complexity affects individual voting behavior, we develop a novel measure of proposition complexity (using official pre-referendum booklets) and combine it with post-referendum survey data from Switzerland. Using Heckman selection estimations to account for endogenous variation in participation rates, we find that an increase in proposition complexity from the 10th to the 90th percentile would decrease voters' approval by 5.6 ppts, which is often decisive: an additional 12% of the propositions in our sample would be rejected.     

Selecting successful students? Undergraduate grades as an admission criterion

In Europe’s reformed education system, universities may be forced by law to consider undergraduate grade point average (UGPA) as the primary admission criterion in the selection of graduate students. In this article, we investigate whether UGPA predicts graduate student performance in order to discuss its usefulness as an admission criterion. In our theoretical framework, we show that undergraduate students may choose slower study progress in favour of receiving higher grades and conclude that UGPA is a relatively good (weak) predictor for graduate grade point average (study progress). Having data from a cohort of students whose selection was in clear conflict with the legal requirement, we empirically confirm our theoretical predictions by exploiting a unique opportunity for assessing educational policies. Discussion of our findings leads to some important conclusions concerning the Bologna reforms and the lawmakers’ idea of giving some independence to universities, but not too much of it.     

Capital adjustment cost and inconsistency in income‐based dynamic panel models with fixed effects

After the seminal work of Nickell (1981), a vast literature demonstrates the inconsistency of ‘conditional convergence’ estimator in income‐based dynamic panel models with fixed effects when the time horizon (T) is short but the sample of countries (N) is large. Less attention is given to the economic root of inconsistency of the fixed effects estimator when T is also large. Using a variant of the Ramsey growth model with long‐run adjustment cost of capital, we demonstrate that the fixed effects estimator of such models could be inconsistent when T is large. This inconsistency arises because of the long‐run adjustment cost of capital which gives rise to a negative moving average coefficient in the error term. Income convergence will be thus overestimated. We theoretically characterize the order of this inconsistency. Our Monte Carlo simulation demonstrates that the size of the bias is substantial and it is greater in economies with higher capital adjustment costs. We show that the use of instrumental variables that take into account the presence of the negative moving average term in the error will overcome this bias.     

The Political Economy of Policy Reform in the Philippines: 1992–1998

Accurately measuring Turkey's informal sector is important for policymaking. We utilize household income‐expenditure surveys to examine this sector's income underreporting. The Pissarides‐Weber approach hypothesizes that data would reflect such underreporting as “excess food consumption”. Our results suggest informal sector members spend more than their formal sector counterparts with comparable reported income levels. Using this information, we estimate the average size of the true informal sector to be about 1.25 times the official estimate. The informal sector accounts for around 83% of officially reported disposable income. Therefore, true Turkish disposable income is (25%)?(83%), roughly 21% larger than the officially estimated magnitude.     

Prediction of Graduate Performance in Economics

Professor Hansen's paper describes an effort to predict the success of graduate students in economics at The University of Wisconsin. Undergraduate grade point average, GRE scores, and the quality of the undergraduate schools were used as independent variables in a linear multiple regression model. Graduate grade point average was the dependent variable. The value of the independent variables as predictors is analyzed both jointly and in isolation. Among the important conclusions reached by Hansen is that heavy reliance upon a single predictor such as the undergraduate grade point average is unwise, that the GRE quantitative score takes on greater significance as the graduate student advances into the second year of his program, and that school quality must be taken into account.     

The role of innovation and quality change in Japanese economic growth

This paper explores the use of time series data to isolate quality change in the Japanese economy using a hedonic procedure. We argue that the traditional approach to hedonic estimation based upon panel data sets of different brands in a given product area is extremely resource intensive and, thus, unlikely to be adopted by official statistical bodies outside of key areas, such as computers. This paper adopts a “top-down” approach to see whether more traditional measures of technical change, such as patents, can be used to separate pure inflation from quality change. If this is possible, it offers a much simpler route to estimate the role of quality change in economic growth and performance. In practice, we extend the analysis not only to include patents, but other forms of intellectual property that might reflect technology and attribute changes, such as designs, utility models and trademarks. We begin by taking a longer-term historical perspective, exploring the development of indigenous inventive capacity in Japan during the early years when R&D data are not available. It is possible to show that the rise in utility models pre-dates the main growth in patenting activity, suggesting the development in more low-level indigenous creative work prior to higher level inventive activity. The principal aim of this paper, however, is to demonstrate that it is possible to develop robust models to explain changes in the producer price index in Japan, which can then be used to re-examine Japanese growth performance over the period from about 1960. If the official Japanese statistical body has fully accounted for quality change in the price indices (i.e. produced fully quality-constant price deflators), then the official estimates of growth will be correct. However, we provide strong evidence that this is not the case. Changes in quality, proxied by the IP variables, are important determinants of prices in Japan over the period 1960 to 1995 as a whole. Indeed, we provide evidence that the true rate of growth of the Japanese economy, taking into account the rate of quality change, is significantly higher than that suggested in official statistics.     

ESTIMATES OF THE HIDDEN ECONOMY IN AUSTRIA ON THE BASIS OF OFFICIAL STATISTICS

By definition, the hidden economy eludes straight observation by means of official statistics. Nevertheless, attempts to quantify these phenomena usually make reference to official materials in various respects, e.g. as regards definition, or when evaluating the relative importance or some indirect reflections of such activities. In this context, official statistics may serve as a particularly useful reference when those sections of the economy are concerned which are hardly or not at all susceptible to hidden activities. Such sections can be identified in terms of industry and in terms of occupation.
In the present investigation such techniques have been used to a large extent and only official statistics have been drawn upon as a data source. Accordingly, the outcome matches closely with national accounts concepts and existing national classifications of various socio-economic statistics. The estimates refer to the hidden ("off the records") activities of the self-employed as well as to similar activities of employees, the unemployed etc. ("moonlighting"). Per se criminal activities have not been included, however. As regards the self-employed the estimates basically rely on income differentials observed between small scale entrepreneurs and their employees. As regards employees numbers employed of various preselected occupational categories and of some additional groups of non-employed have been processed successively, matching them e.g. with comparable data on time budgets and regional frequency.
The outcome largely confirms common experience or expectations as regards the fields where hidden activities assume significant relative importance whereas the overall size of the hidden economy turned out fairly small as compared with official GDP.     

GOVERNMENT TRANSPARENCY AND EXPENDITURE IN THE RENT‐SEEKING INDUSTRY: THE CASE OF JAPAN FOR 1998–2004

Since the end of the 1990s, local governments in Japan have enacted Information Disclosure Ordinances, which require the disclosure of official government information. This article uses Japanese prefecture‐level data for the period 1998–2004 to examine how this enactment affected the rate of government construction expenditure. The Dynamic Panel model is used to control for unobserved prefecture‐specific effects and endogenous bias. The major finding is that disclosure of government information reduces the rate of government construction expenditure. This implies that information disclosure reduces losses from rent‐seeking activity, which is consistent with public choice theory. (JEL D73, D78, H79)     

ARE SURVEYS OF EXPERTS UNBIASED? EVIDENCE FROM COLLEGE FOOTBALL RANKINGS

Policymakers are frequently interested in soliciting unbiased information regarding alternative policies, and expert surveys can be influential. As ranking policies is an often subjective process, there is always the concern of bias, both intentional and not. Expert bias is difficult to discern in the policy world, but surveys of expert opinion are compiled and “tested” for accuracy weekly in college football, allowing for hypothesis testing. Although previous research has used college football rankings to determine the ability of surveys to incorporate relevant information, this article examines the Associated Press and American Football Coaches' Association rankings for evidence of systematic bias. Specifically, more than 1,300 games from the 2003 to 2008 regular seasons are tested for factors that are systematically correlated with upsets. Both polls predict the winner nearly 80% of the time, and although there is evidence of systematic conference bias, correcting the rankings would only improve the accuracy of the polls by about 1%. There is no evidence of a bias favoring “big market” teams, nor teams that have strong journalism programs or are from the East Coast. (JEL D4, L8)     

Poverty Mapping with Aggregate Census Data: What is the Loss in Precision?

Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some countries (notably China and India), national statistics agencies are reluctant, for reasons of confidentiality, to release household‐level census data, but they are generally more willing to release aggregated census data, such as village‐ or district‐level means. This paper examines the loss in precision associated with using aggregated census data instead of household‐level data to generate poverty estimates. The authors show analytically that using aggregated census data will result in poverty rates that are biased downward (upward) if the rate is below (above) 50%, and that the bias approaches zero as the poverty rate approaches zero, 50%, and 100%. Using data from Vietnam, it is found that the mean absolute error in estimating district‐level poverty rates is 2.5 percentage points if the census data are aggregated to the enumeration‐area level means, and 3–4 percentage points if the data are aggregated to commune or district level. Finally, the authors propose a method for reducing the error using variances calculated from the census. When this approach is applied to the Vietnam data, this method can cut the size of the aggregation errors by around 75%.     

Model Uncertainty, Optimal Monetary Policy and the Preferences of the Fed

Monetary policy in the US is characterized by a substantial degree of inertia. While in principle this may well be the outcome of an optimizing central bank behaviour, the ability of any derived policy rule to match the data relies on so large weights for interest rate smoothing into policy makers' preferences as to be theoretically flawed. In this paper we investigate whether such a puzzle can be interpreted as resulting from the concern of monetary authorities for potential misspecifications of the macroeconomic dynamics. Accordingly, we propose a novel thick modelling approach that incorporates model uncertainty into the identification of central bank's preferences. The thick robust policy rule shows the kind of smoothness observed in the data without resorting to implausible values for the preference parameters.     

Forecasting revisions of German industrial production

Macroeconomic variables, such as industrial production or GDP, are regularly and sometimes substantially revised by the official statistical offices. Nevertheless, there are only few attempts in the previous literature to investigate whether it is possible to forecast these revisions systematically. In this article, it is illustrated how revisions of German industrial production can be forecasted with respect to both the direction and the level of the revision. We are the first to use a large data set for this purpose.     

《洛阳名园记》之刘氏园归属考辨

陈植怀疑刘氏园之“刘给事”为北宋官员刘元瑜,但有学者提出异议。对此,先推勘刘氏园主应具备的条件;再从陈植论据的适用性、正确性以及史籍中刘元瑜的称谓等处辨证其观点的错误;最后从园林沿革以及园主称谓、居处等方面对刘氏园归属进行考证,认为“刘给事”应是宋初给事中刘载,李格非写就《洛阳名园记》时,刘氏园归刘载后人所有。     

On the informational content of advice: a theoretical and experimental study

This paper examines the market for advice and the underlying perception that advice is useful and informative. We do this by first providing a theoretical examination of the informational content of advice and then by setting up a series of experimental markets where this advice is sold. In these markets we provide bidders with a demographic profile of the “experts” offering advice.The results of our experiment generate several interesting findings. The raw bid data suggest that subjects bid significantly more for data than they do for advice. Second, in the market for advice there appears to be no consensus as to who are the best advisors although on average economists demand the highest mean price and women suffer a discount. In addition, we find that whether a subject suffers from a representativeness bias in the way he or she processes data has an impact on how he or she bids for advice and on his or her willingness to follow it once offered. Finally, we find that on average people impute a low level of informativeness onto advice, consistent with their bidding behavior for data versus advice.This work was done under grant number SES-0425118 of the National Science Foundation. The authors would like to recognize the Center for Experimental Social Science at New York University for its additional support. We also acknowledge the help of Elizabeth Potamites for her research assistance.     

MODELING ON THE BASIS OF MODELS

A large part of official economic data sets is produced with the help of assumed functional relations between variables. Constructing economic models on the basis of such model-generated data results in a "modeling on the basis of the results of modeling." This common procedure can lead to consequences that seriously endanger the quality of empirical analyses. After discussing some of these dangerous consequences the authors explore the reasons behind this development. To avoid some of the most severe difficulties a "Charter for Compilation and Correct Handling of Economic Data" is proposed.     

Dynamic specification of demand functions: A cointegration approach

The single-equation approach has been commonly used in the studies of energy demand. However, as most of the data used in the energy demand model are unlikely to be stationary, this factor has to be taken into account when estimating the demand behavior. To overcome this problem, the authors have applied the cointegration and error-correction models to model Chinese coal consumption data. In order to contrast their performance with such traditional models as Hendry's general-to-specific approach, a forecast error comparison exercise has been conducted. In terms ofex post forecast errors, the Engle-Granger error correction model outperforms other chosen models. By using the Engle-Granger approach, it is possible to obtain important information about the behavior of coal demand in China.     

The methodology used by Russian statistical bodies to analyse small business

Assessing the level of development of small business in Russia requires a critical analysis of official statistics, owing to the existence of several inconsistencies. In addition, the frequent changes in the methodology make it difficult to compare the data over a period. It must also be taken into account that Russian and Western official data on small business are not fully comparable, as the Russian definition of small business has several limitations. For this reason its contribution to the economy is understated. Officially, employment in small businesses has stopped growing since 1994. Survey‐based results, however, point to a continuous increase in the number of people employed by new private enterprises, suggesting that the emergence of entrepreneurship has been an organic process, as in the leading transition countries, although it has been much slower in Russia.     

Misreporting in register data on disability status: evidence from the Swedish Public Employment Service

The issue considered in this study is whether there is misreporting in official data on disability status. While there is a rather large literature on misreporting of self-assessed disability, evidence regarding register data is scant. It seems to be a widely held view among researchers that, since individuals out of work are inclined to respond towards poor health, it would be best to have official data provided by the relevant administrative bodies. But we argue that such administrative data should be regarded with some suspicion, since the administrators also may have incentives to misreport. The empirical evidence, based on a large sample of Swedish jobseekers, suggests systematic misreporting by the Public Employment Service of official disability measures due to incentives to misreport disability.