Compensating Wage Differentials with Unemployment: Evidence from China

We estimate the economic value of mortality risk in China using the compensating-wage-differential method. We find a positive and statistically significant correlation between wages and occupational fatality risk. The estimated effect is largest for unskilled workers. Unemployment reduces compensation for risk, which suggests that some of the assumptions under which compensating wage differentials can be interpreted as measures of workers’ preferences for risk and income are invalid when unemployment is high. Workers may be unwilling to quit high-risk jobs when alternative employment is difficult to obtain, violating the assumption of perfect mobility, or some workers (e.g., new migrants) may be poorly informed about between-job differences in risk, violating the assumption of perfect information. These factors suggest our estimates of the value per statistical life (VSL) in China, which range from approximately US$30,000 to US$100,000, may be biased downward. Alternative estimates adjust for heterogeneity of risk within industry by assuming that risk is concentrated among low-skill workers. These estimates, which are likely to be biased downward, range from US$7,000 to US$20,000.      

General equilibrium impact of an energy-saving policy in the public sector

We analyse a disregarded environmental policy instrument: a switch in government expenditure away from energy (or other natural resources) and toward a composite good which includes energy-saving expenditure. We first develop two variants of an analytical general equilibrium model. A composite good is produced with constant returns to scale, and energy is imported or produced domestically with diminishing returns, yielding a differential rent to its owners. The government purchases energy and composite goods from private firms. Such a policy unambiguously increases employment. It also raises private consumption and welfare under two conditions: (i) it is not too costly and (ii) the initial share of the resource is smaller in public spending than in private consumption, or the difference is small enough. We then run numerically a model featuring both importation and domestic production of energy (oil, gas and electricity), for the OECD as a whole. Simulations show that employment, welfare and private consumption rise. We provide magnitudes for different parameter values. Earlier versions of this paper have benefited from conference participants at the European Council for an Energy-Efficient Economy, International Society for Ecological Economics World Congress, CIRED seminar and EUREQua environmental economics seminar. We especially thank Michèle Sadoun and two anonymous referees. The usual disclaimer applies.     

Estimators for the common principal components model based on reweighting: influence functions and Monte Carlo study

The common principal components model for several groups of multivariate observations is a useful parsimonious model for the scatter structure which assumes equal principal axes but different variances along those axes for each group. Due to the lack of resistance of the classical maximum likelihood estimators for the parameters of this model, several robust estimators have been proposed in the literature: plug-in estimators and projection-pursuit (PP) type estimators. In this paper, we show that it is possible to improve the low efficiency of the projection-pursuit estimators by applying a reweighting step. More precisely, we consider plug-in estimators obtained by plugging a reweighted estimator of the scatter matrices into the maximum likelihood equations defining the principal axes. The weights considered penalize observations with large values of the influence measures defined by Boente et al. (2002). The new estimators are studied in terms of theoretical properties (influence functions and asymptotic variances) and are compared with other existing estimators in a simulation study.     

Wage inequality in developing countries: South–South trade matters

The relationship between trade liberalization and inequality has received considerable attention in recent years. The major purpose of this study is to present new results on the sources of wage inequalities in manufacturing taking into account South–South (S–S) trade. Globalization has not only lead to increasing North–South (N–S) trade, but it has also changed the direction and composition of trade as more trade is carried out among developing countries. In this study, we find that increasing wage inequality is associated more with the South–South trade liberalization than with the classical trade liberalization with northern countries. A part of this increasing wage inequality due to S–S trade comes from the development of N–S trade relationship in S–S trade that increases wage inequality in middle-income developing countries. This study also seeks to shed some light on the link between the direction of trade and technological change. We explore the fact that S–S trade leads to a technological change biased toward skill-intensive sectors more than N–S trade. This indirect effect increases wage inequality for all developing countries, but it is more important in low-income countries.     

Panel Data Analysis of Regional Differentials in the Registered Voter Turnout Rate and the Expected Benefits of Voting for Minorities

Voter participation rates vary widely across the 50 states. We seek to identify a source of this interstate variation, focusing upon the 2000, 2004, 2008, and 2012 general elections. Of note is that the latter two general elections featured a minority (i.e., African-American) nominee for president from one of the major political parties. Within the context of the rational voter model, we hypothesize that the presence of a minority candidate atop the ticket will boost minorities’ expected net benefits from voting, with the result that minority voter participation will be higher. Based on cross-sectional fixed-effects estimations, we find that states’ voter participation rates were unaffected by the percent of the population that was either African-American or Hispanic for the 2000 and 2004 election cycles, while states’ voter participation rates were positively related to the percent of the population that was either African-American or Hispanic for the 2008 and 2012 election cycles.     

The behaviour of producer prices: evidence from French PPI micro data

This paper provides some new empirical findings for how French producers set prices. We used the micro data that composes the producer and business-service price indices from 1994 to 2005. First we address how producer prices are collected. Then we present the main characteristics of how producers change their prices: they are modified infrequently and in small amounts. Also, a behavioural heterogeneity across sectors is observed. Business-service prices change less often than industrial producer prices. The data corroborates both time and state-dependent model predictions. Taylor contracts are not unusual, but a firm’s prices will also react to its economic situation. Nevertheless, the most relevant models, to explain producer price rigidity, are time-dependent.

“The fact that some prices are rigid or sticky, while others are variable, has attracted a good deal of comments from economists in recent years” Tucker (1938)

This study was conducted in the context of the Eurosystem Inflation Persistence Network. Data were processed under the responsibility of INSEE in the context of an agreement between INSEE and the Banque de France (20B-21B-E301/R05019/2005).     

A generalization to QUAIDS

Previous research shows that consumers’ response to price and income changes is heterogeneous. In addition, evidence from national data often does not support the classical assumption of one commodity-one price. This paper introduces a data coherent generalization to the quadratic form of the almost ideal demand system (g-QUAIDS) that incorporates the sources of heterogeneity in the demand function and allows for regional price variation. Aggregation over consumers imposes a linearization to the g-QUAIDS that requires a new set of price indices. The results from an empirical study by using microdata from the Household Income and Expenditure Survey of Iran highlight the impact of aggregation bias in relation to the level of aggregation. An investigation of the predictive power of linear versus nonlinear g-QUAIDS in different aggregation levels provides practical recommendations for consumer demand analysis.     

Social Ties and the Demand for Financial Services

This paper studies the importance of social interactions for the adoption of financial services among young adults. Specifically, we investigate whether, how, and why financial decisions among interacting agents are correlated. We exploit a unique dataset of friendship networks in the United States and a novel estimation strategy that accounts for possibly endogenous network formation. We find that not all social contacts are equally important: only long-lasting relationships influence financial decisions. Moreover, this peer influence exists only in cohesive social structures. This evidence is consistent with an important role of trust in financial decisions. When agents consider whether or not to adopt a financial instrument, they face a risk and may place greater value on information coming from agents they trust. These results can help explain the importance of face-to-face social contacts for financial decisions.     

Do missing values exist? Incomplete data handling in cross-national longitudinal studies by means of continuous time modeling

In cross-national longitudinal studies it is often impossible to administer the same measurement instruments at the same occasions to all sample units in all participating countries. This quickly results in large quantities of missing data, due to (a) missing measurement instruments in some countries, (b) missing assessment waves within or across countries, (c) missing data for individual sample units. As compared to cross-sectional studies, the problem of missing values is further aggravated by the fact that missing values are always associated with different time intervals between repeated observations. In the past, this has often been dealt with by the use of phantom-variables, but this approach is limited to simple designs with few missing value patters. In the present paper we propose a new way to think of, and deal with, missing values in longitudinal studies. Instead of conceiving of a longitudinal study as a study with \(T\) discrete time points of which some are missing, we propose to conceive of a longitudinal study as a way to measure an underlying process that develops continuously over time, but is only observed at some selected discrete time points. This transforms the problem of missing values into a problem of unequal time intervals. After a quick introduction to the basic idea of continuous time modeling, we demonstrate how this approach provides a straightforward solution to missing measurement instruments in some countries, missing assessment waves within or across countries, and missing data for individual sample units.