By Marc Nerlove, Patrick Sevestre, Pietro Balestra (auth.), László Mátyás, Patrick Sevestre (eds.)

ISBN-10: 3540758895

ISBN-13: 9783540758891

ISBN-10: 3540758925

ISBN-13: 9783540758921

This thoroughly restructured, up-to-date 3rd variation of The Econometrics of Panel facts, first released in 1992, offers a basic review of the econometrics of panel info, either from a theoretical and from an utilized perspective. because the pioneering papers by means of Kuh, Mundlak, Hoch and Balestra and Nerlove, the pooling of go part and time sequence info has develop into an more and more renowned method of quantifying monetary relationships. every one sequence presents details missing within the different, so a mixture of either results in extra exact and trustworthy effects than will be available by means of one kind of sequence by myself.

This 3rd, more advantageous version offers an entire and recent presentation of theoretical advancements in addition to surveys approximately how econometric instruments are used to check corporations and household’s behaviors. It comprises 11 solely new chapters whereas the others were principally revised to account for fresh advancements within the field.

**Read or Download The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice PDF**

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**Additional resources for The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice**

**Sample text**

However, an exception to this rule is if, for the particular sample of individuals we have drawn (now we can specifically identify each), we want to predict future values of yit for that individual. Second, since the xit are themselves considered to be stochastic, for each individual their values over time will in general be correlated. There may also be correlations among xit ’s for different values of i if different individuals have some characteristics in common. But we neglect this possibility here.

T . 13) If only semi-asymptotics on N is considered (T finite), we need not assume | α |< 1. On the other hand, the process generating the initial observations is very important. As suggested above, this means that the individuals’ past history with respect to both the observed variables x and the latent variables ε becomes crucial. 14) t−1 ∑ α j εi,t− j . j=0 Thus, each observation on the dependent variable yit can be written as the sum of four terms: The first, α t yi0 , depends on the initial values which, as long as T is finite, do influence the behavior of any estimators.

Suppose that we draw a random sample of N individuals over T time periods; for example a household survey in which we collect observations on the income, xit and consumption of household i, yit , for many households N, in year t over a brief period T . From the survey we have observations on the pairs (xit , yit ). Since the households are chosen at random for the survey, but the years over which they are observed are not, the lists (xi1 , yi1 , . . , xiT , yiT ), i = 1, . . , N, are exchangeable, but the order within each list is not.

### The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice by Marc Nerlove, Patrick Sevestre, Pietro Balestra (auth.), László Mátyás, Patrick Sevestre (eds.)

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