Modelling commodity demands and labour supply with m-demands

In the empirical modelling of demands and labour supply we often lack data on a full set of goods. The usual response is to invoke separability assumptions. Here we present an alternative based on modelling demands as a function of prices and the quantity of a reference good rather than total expenditure. We term such demands m-demands. The advantage of this approach is that we make maximum use of the data to hand without invoking implausible separability assumptions. In the theory section quasi-Slutsky conditions are derived and some structural and separability conditions are presented. We also derive functional forms for empirical work. Finally an empirical illustration on Canadian expenditure data is given. This illustrates both the implementation of the ideas presented in the theory section and the empirical costs of not having a full set of data.consumer demands; labour supply; Slutsky conditions

Dynamic binary outcome models with maximal heterogeneity

Most econometric schemes to allow for heterogeneity in micro behaviour have two drawbacks: they do not fit the data and they rule out interesting economic models. In this paper we consider the time homogeneous first order Markov (HFOM) model that allows for maximal heterogeneity. That is, the modelling of the heterogeneity does not impose anything on the data (except the HFOM assumption for each agent) and it allows for any theory model (that gives a HFOM process for an individual observable variable). `Maximal' means that the joint distribution of initial values and the transition probabilities is unrestricted. We establish necessary and sufficient conditions for the point identification of our heterogeneity structure and show how it depends on the length of the panel. A feasible ML estimation procedure is developed. Tests for a variety of subsidiary hypotheses such as the assumption that marginal dynamic effects are homogeneous are developed. We apply our techniques to a long panel of Danish workers who are very homogeneous in terms of observables. We show that individual unemployment dynamics are very heterogeneous, even for such a homogeneous group. We also show that the impact of cyclical variables on individual unemployment probabilities differs widely across workers. Some workers have unemployment dynamics that are independent of the cycle whereas others are highly sensitive to macro shocks

Unemployment Insurance Benefit Levels and Consumption Changes.

We use a Canadian survey of the unemployment to examine how household expenditures after a job loss respond to the level of income replacement provided by UI.UNEMPLOYMENT INSURANCE ; LIVING STANDARDS ; CONSUMPTION; Liquidity constraints

Shocks, Stocks and Socks

Recent research has demonstrated that some households cut back on expenditures in an unemployment spell. Moreover, some of these households respond to variation in the transitory income provided by unemployment insurance benefits. This suggests that these households are constrained in the sense that they respond to variations in current income even if these do not have any permanent impact. In this paper we take up the question of how households in temporarily straitened circumstances cut back and how they spend marginal dollars of transfer income. Our theoretical and empirical analysis emphasises the importance of allowing for the fact that households buy durable as well as non-durable goods. The theoretical analysis shows that in the short run households can significantly cut back on total expenditures without a significant fall in welfare if they concentrate their budget reductions on durables. We present an empirical analysis based on a Canadian survey of workers who experienced a job separation. Exploiting changes in the unemployment insurance system over our sample period we show that cuts in UI benefits lead to reductions in total expenditure with a stronger impact on clothing than on food expenditures. These effects are particularly strong for households with no liquid assets and/or households in which the lost income was ‘important’ for the household. These findings are in precise agreement with the theoretical predictions.

Shocks, stocks and socks: consumption smoothing and the replacement of durables during an unemployment spell

We present theoretical and empirical results on consumption during an unemployment spell. The theory model extends the conventional intertemporal allocation model to take explicit account of the fact that households buy clothing and small durable goods (such as pillows and plates) that are indivisible, irreversible and non-collateralisable. The theoretical analysis suggests that liquidity constrained agents cut back on expenditures on these small durables during a low income spell much more than would be suggested by the income elasticities of these goods in 'normal' times. Conversely, non-durable expenditures flows are much smoother than would be predicted in a model without durables. Thus it seems that agents can smooth utility flows even when total expenditure (on durables and non-durables) is quite volatile. The implications of this model are compared to the implications from three other widely used models of intertemporal allocation. In the empirical section, we exploit the information in a new Canadian panel survey of 20,000 workers who separated from a job in 1993 or 1995. As well as conventional survey information, this survey includes expenditure and asset information. Administrative data from several sources are linked to this panel to provide a detailed picture of the circumstances of households in which one member is unemployed. We estimate a joint total expenditure and demand system and test whether either the level of total expenditure or the structure of demand are sensitive to differences in the Unemployment Insurance benefit rate. We find that they are for households who have no liquid assets. Of the models that we consider, only the intertemporal allocation model proposed in this paper is consistent with this finding.

Pooling of Income and Sharing of Consumption within Households

There are extensive literatures within economics and economic psychology on the allocation of household income within the household. These two literatures are largely disjoint but both use a concept of ‘income pooling’. In economics this refers to the independence of household decisions from who receives the income within the household. In economic psychology it refers to the management of household finances. This article uses a new Danish expenditure survey that gives information on both concepts and on the assignment of expenditures to consider the link between the two. More importantly, we investigate whether either type of pooling is related to the sharing of expenditures between the two partners. We find that sharing does depend on who receives the income within non-pooling households, but not on the economic psychological income pooling regime per se.household production and intra-household allocation; personal income; wealth and their distributions; methodology for collecting, estimating, and organizing microeconomic data; marriage and family

Heterogeneity and Microeconometrics Modelling

Presented at the 2005 Econometric Society World Congress Plenary Session on "Modelling Heterogeneity". We survey the treatment of heterogeneity in applied microeconometrics analyses. There are three themes. First, there is usually much more heterogeneity than empirical researchers allow for. Second, the inappropriate treatment of heterogeneity can lead to serious error when estimating outcomes of interest. Finally, once we move away from the traditional linear model with a single 'fixed effect', it is very difficult to account for heterogeneity and fit the data and maintain coherence with theory structures. The latter task is one for economists: "heterogeneity is too important to be left to the statisticians". The paper concludes with a report of our own research on dynamic discrete choice models that allow for maximal heterogeneity.heterogeneity; applied microeconometrics; fixed effects; dyanamic discrete choice

Are two cheap, noisy measures better than one expensive, accurate one?

1. Survey responses are always subject to measurement error. In general surveys (and especially longitudinal surveys), there are severe constraints on the time that can be spent eliciting a less noisy response for any target variable. In this paper we consider when it may be better to consider multiple noisy measures of the target measure rather than improving the reliability of a single measure. 2. The Kotlarski result states that if the measurement errors in two measures of the same target variable are mutually independent and independent of the true value then we can recover the entire distribution of the quantity of interest, up to location. 3. We consider designing surveys to deliver measurement error with desirable properties. This shifts the emphasis from reliability (the signal to noise ratio for any given measure) to the joint properties of the multiple measures. 4. To illustrate our ideas, we consider a concrete example: the measurement of consumption inequality. A small simulation study suggests that the approach we propose has promise. The next step in this research agenda is experiments in survey data collection.

Dynamic binary outcome models with maximal heterogeneity

Most econometric schemes to allow for heterogeneity in micro behaviour have two drawbacks: they do not fit the data and they rule out interesting economic models. In this paper we consider the time homogeneous first order Markov (HFOM) model that allows for maximal heterogeneity. That is, the modelling of the heterogeneity does not impose anything on the data (except the HFOM assumption for each agent) and it allows for any theory model (that gives a HFOM process for an individual observable variable). `Maximal' means that the joint distribution of initial values and the transition probabilities is unrestricted. We establish necessary and sufficient conditions for the point identification of our heterogeneity structure and show how it depends on the length of the panel. A feasible ML estimation procedure is developed. Tests for a variety of subsidiary hypotheses such as the assumption that marginal dynamic effects are homogeneous are developed. We apply our techniques to a long panel of Danish workers who are very homogeneous in terms of observables. We show that individual unemployment dynamics are very heterogeneous, even for such a homogeneous group. We also show that the impact of cyclical variables on individual unemployment probabilities differs widely across workers. Some workers have unemployment dynamics that are independent of the cycle whereas others are highly sensitive to macro shocks.Discrete choice, Markov processes, Nonparametric identification, Unemployment dynamics