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Conventional methods to test for long-term PPP based on the theory of cointegration are typically undertaken in the framework of vector error correction models (VECM). The standard approach in the use of VECMs is to employ a model of full-order, which assumes nonzero entries in all the coefficient matrices. But, the use of full-order VECM models may lead to incorrect inferences if zero entries are required in the coefficient matrices. Specifically, if we wish to test for indirect causality, instantaneous causality, or Granger non-causality, and employ “overparameterised” full-order VECM models that ignore entries assigned a priori to be zero, then the power of statistical inference is weakened and the resultant specifications can produce different conclusions concerning the cointegrating relationships among the variables. In this paper, an approach is presented that incorporates zero entries in the VECM analysis. This approach is a more straightforward and effective means of testing for causality and cointegrating relations. The paper extends prior work on PPP through an investigation of causality between the U.S. Dollar and the Japanese Yen. The results demonstrate the inconsistencies that can arise in the area and show that bi-directional feedback exists between prices, interest rates and the exchange rate such that adjustment mechanisms are complete within the context of PPP.

In this paper we consider two traffic control strategies relying on user response to information and/or flow restriction. Ultimately, the control strategies are designed to function in real time, hence provide command values based on actual conditions and requiring little computational effort. The proposed control strategies are based on the idea that the network load, as measured by instantaneous travel times for instance, should be shared as equally as possible between paths. In order to achieve such an aim, the commands are designed to make the system state converge towards a state in which instantaneous travel times of paths relative to any given OD tend to be equal.

This chapter analyzes detailed 24-hour diary data from the United States to provide evidence on the relationship between workers' effort and well-being while at work. In doing so, we first measure workers' effort in terms of the amount of on-the-job leisure, number of on-the-job leisure episodes, and the time working until consuming on-the-job leisure. Second, we link these three measures of worker effort to data on instantaneous well-being while at work. We find that the less time devoted to on-the-job leisure and the number of on-the-job leisure episodes, and the more time workers spend working until on-the-job-leisure, the higher the levels of stress during their work tasks. In analyzing workers' effort and stress during market work activities, we contribute to the scant literature on the determinants of worker happiness while at work, positing the consumption and the frequency of on-the-job leisure as affective factors.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

The paper published below was prepared by Taylor Ostrander for Frank Knight’s course, Economic Theory, Economics 301, during the Fall 1933 quarter.

The same forces that lead to changes in participation in the labor market can also affect the extent of criminal activity. To analyze such interaction we construct a search-theoretic model where labor market participation, labor market outcomes and crime are determined jointly. The model is calibrated to US data focusing on females. The main finding is that changes affecting the labor market, such as changes in productivity or in preferences toward market activities, can have significant effects on criminal behavior.