We test for price discontinuities, or jumps, in a panel of high-frequency intraday stock returns and an equiweighted index constructed from the same stocks. Using a new test for common jumps that explicitly utilizes the cross-covariance structure in the returns to identify non-diversifiable jumps, we find strong evidence for many modest-sized, yet highly significant, cojumps that simply pass through standard jump detection statistics when applied on a stock-by-stock basis. Our results are further corroborated by a striking within-day pattern in the significant cojumps, with a sharp peak at the time of regularly scheduled macroeconomic news announcements. r
We test for price discontinuities, or jumps, in a panel of high-frequency intraday stock returns and an equiweighted index constructed from the same stocks. Using a new test for common jumps that explicitly utilizes the cross-covariance structure in the returns to identify non-diversifiable jumps, we find strong evidence for many modest-sized, yet highly significant, cojumps that simply pass through standard jump detection statistics when applied on a stock-by-stock basis. Our results are further corroborated by a striking within-day pattern in the significant cojumps, with a sharp peak at the time of regularly scheduled macroeconomic news announcements. r
Does the market allocate the right workers to the right jobs? Since observable (to economists) variables account for only a small fraction of the wage variance in the data, to answer this question it is essential to study assortative matching between employers and employees based on their unobserved characteristics. This paper enables this line of research. We show theoretically that all parameters of the classic model of sorting based on absolute advantage in Becker (1973) with search frictions can be identified using only matched employer-employee data on wages and labor market transitions. In particular, these data are sufficient to assess whether matching between workers and firms is assortative, whether sorting is positive or negative, and to measure the potential effect on output from moving any given worker to any given employer in the economy. We provide computational algorithms that implement our identification strategy given the limitations of the available data sets. Finally, we extend our identification and implementation strategies to the commonly used class of models of sorting based on comparative advantage and provide a test that discriminates between these models.
The supplement contains most formal proofs and derivations (Section A), detailed description of implementation strategy and computational algorithms (Sections B and C), complete specification of the model with on-the-job search and the identification proof for this model (Section D), details of empirical analysis using large German matched employer-employee data (Section E), and figures describing Monte Carlo results for the benchmark model and various alternative specifications (Section F).
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