Showing results 1 to 5 of approximately 5.(refine search)
Sellin’ in the Rain: Adaptation to Weather and Climate in the Retail Sector
Using novel methodology and proprietary daily store-level sporting goods and apparel brand data, I find that, consistent with long-run adaptation to climate, sales sensitivity to weather declines with historical norms and variability of weather. Short-run adaptation to weather shocks is dominated by changes in what people buy and how they buy it, with little intertemporal substitution. Over four weeks, a one-standard deviation one-day weather shock shifts sales by about 10 percent. While switching between indoor and outdoor stores offsets a small portion of contemporaneous responses to ...
A Coherent Framework for Predicting Emerging Market Credit Spreads with Support Vector Regression
We propose a coherent framework using support vector regression (SRV) for generating and ranking a set of high quality models for predicting emerging market sovereign credit spreads. Our framework adapts a global optimization algorithm employing an hv-block cross-validation metric, pertinent for models with serially correlated economic variables, to produce robust sets of tuning parameters for SRV kernel functions. In contrast to previous approaches identifying a single "best" tuning parameter setting, a task that is pragmatically improbable to achieve in many applications, we proceed with ...
Dynamic Econometrics in Action: A Biography of David F. Hendry
David Hendry has made–and continues to make–pivotal contributions to the econometrics of empirical economic modeling, economic forecasting, econometrics software, substantive empirical economic model design, and economic policy. This paper reviews his contributions by topic, emphasizing the overlaps between different strands in his research and the importance of real-world problems in motivating that research.
Jargon Alert on Machine Learning
Understanding Survey Based Inflation Expectations
Survey based measures of inflation expectations are not informationally efficient yet carry important information about future inflation. This paper explores the economic significance of informational inefficiencies of survey expectations. A model selection algorithm is applied to the inflation expectations of households and professionals using a large panel of macroeconomic data. The expectations of professionals are best described by different indicators than the expectations of households. A forecast experiment finds that it is difficult to exploit informational inefficiencies to improve ...