Econometricians long thought of identification as a binary event: a parameter is either identified or not. Empirical researchers combined available data with assumptions that yield point identification, and reported point estimates of parameters. Yet there is enormous scope for fruitful inference using weaker and more credible assumptions that partially identify parameters. Until recently, stud...

In this paper, I give a personal view on the development of the field of spatial econometrics during the past 30 years. I argue that it has moved from the margins to the mainstream of applied econometrics and social science methodology. I distinguish three broad phases in the development, which I refer to as preconditions, take off and maturity. For each of these phases I describe the main meth...

This paper reviews a number of conceptual issues pertaining to the implementation of an explicit “spatial” perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theory-driven as well as from a data-driven perspective. Considerable attention is paid to the inferential framework necessary to carry out estimat...

The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding very reliable inference, some precautions should be taken in order to ensure this. Two “Golden Rules” are formulated that, if observed, help to obtain the best the bootstrap can offer. Bootstrapping always involves setting up a bootstrap data-generating process (DGP). The main typ...

This chapter reviews the econometric issues involved in estimating models of the competitive acquisition of military capability. Econometrics involves the synthesis of theory, data and statistical methods thus in reviewing the econometrics of arms races, we will pay as much attention to theory and data as we do to statistical methods. After discussing the choice of data and the theoretical issu...

The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. The paper discusses Monte Carlo tests, several types of bootstrap test, an...

Many questions in economics involve long-run or “trend” variation and covariation in time series. Yet, time series of typical lengths contain only limited information about this long-run variation. This paper suggests that long-run sample information can be isolated using a small number of low-frequency trigonometric weighted averages, which in turn can be used to conduct inference about long-r...

Identification in econometric models maps prior assumptions and the data to information about a parameter of interest. The partial identification approach to inference recognizes that this process should not result in a binary answer that consists of whether the parameter is point identified. Rather, given the data, the partial identification approach characterizes the informational content of ...

Abstract The paper illustrates how econometricians practice their subject, using primarily graphical tools. It is based on software which exploits the Windows operating system to show data, results, reports, and graphics simultaneously on screen, and seeks to capture the interactions which were used in the associated lecture to highlight the learning process involved in econometric modelling. T...