Found 7 article(s) for author 'measurement'

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale. Edward Glaeser, Michael Luca, 2017, Paper, “Can new data sources from online platforms help to measure local economic activity at scale? Government datasets from agencies such as the U.S. Census Bureau have long been the gold standard for measuring economic activity at the local level. However, these statistics typically appear only after multi-year lags, and the public-facing versions are aggregated to the county or ZIP code level. In contrast, crowdsourced data from online platforms such as Yelp are often contemporaneous and geographically finer than official government statistics. In this paper, we present evidence that Yelp data can complement government surveys by measuring economic activity in close to real time, at a granular level.Link

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Identification and Estimation of Dynamic Causal Effects in Macroeconomics

Identification and Estimation of Dynamic Causal Effects in Macroeconomics. James Stock, June 8, 2017, Paper, “An exciting development in empirical macroeconometrics is the increasing use of external sources of as-if randomness to identify the dynamic causal effects of macroeconomic shocks. This approach – the use of external instruments – is the dynamic, macroeconometric counterpart of the highly successful strategy in microeconometrics of using external as-if randomness to provide instruments that identify causal effects. This lecture provides conditions on instruments and control variables under which external instrument methods produce valid inference on dynamic causal effects, that is, structural impulse response function; these conditions can help guide the search for valid instruments in applications.Link

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Underestimating the Real Growth of GDP, Personal Income and Productivity

Underestimating the Real Growth of GDP, Personal Income and Productivity. Martin Feldstein, March 2017, Paper, “The problems involved in estimating real output that I discuss in this paper cause the official government statistics to underestimate of the rates of growth of real GDP, real personal income, and productivity. That underestimation is important not just to economists trying to understand where the economy is going but also to the broader public and to the political system.  The understatement of real growth reflects the enormous difficulty of dealing with quality change and the even greater difficulty of measuring the value created by the introduction of new goods and services. Despite the vast amount of attention that has been devoted to this subject in the economic literature and by the government agencies, there remains insufficient understanding of just how imperfect the official estimates actually are. It is important for economists to recognize the limits of our knowledge and to adjust public statements and policies to what we can know.” Link

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The World Klems Initiative: Measuring Productivity at the Industry Level

The World Klems Initiative: Measuring Productivity at the Industry Level. Dale Jorgenson, February 2017, Paper, “The World KLEMS Initiative was established at the First World KLEMS Conference at Harvard University in August. The purpose of this Initiative is to generate industry-level data on outputs, inputs, and productivity. Productivity is defined as output per unit of all inputs. The inputs consist of capital (K) and labor (L), the primary factors of production, and intermediate inputs of energy (E), materials (M), and services (S). The acronym KLEMS describes these inputs.  Industry-level data have been proved to be indispensable for analyzing the sources of economic growth for countries around the world.Link

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How to use economic theory to improve estimators – Supplementary Appendix

How to use economic theory to improve estimators – Supplementary Appendix. Maximiliam Kasy, November 6, 2016, Paper, “This appendix provides some additional discussion, supplementing the manuscript of “How to use economic theory to improve estimators.” Our theoretical results suggest that the proposed empirical Bayes estimators should uniformly outperform unrestricted estimators and outperform structural (restricted) estimators for most parameter values. In Section A, we discuss some Monte Carlo simulations which do indeed confirm these predictions.Link

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Happiness and social institutions

Happiness and social institutions. Amartya Sen, 2016, Book Chapter, “Dante lamented in The Divine Comedy, ‘Born to ascend on the wings, / Why do ye fall at such a little wind?’1 Why indeed? The contrast between the great things human beings can achieve and how limited the lives most men and women end up having is truly remarkable. Dante’s question, from the early fourteenth century, remains very much alive even today. The potentialities of human beings to lead a good life, to be contented and happy, to be free to choose the kind of life they want to have far exceed what typically we, in fact, manage to do.Link

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Econometric Tools for Analyzing Moment Inequalities

Econometric Tools for Analyzing Moment Inequalities. Ariel Pakes, August 2016, Paper, “Griliches Lectures, Kyoto. Adjust for Different Variance of Different Moments. Assume that a consistent estimator of the diagonal matrix consisting of the square root of the moments evaluated at each θ is available. Call that estimate ˆDJ(θ)(a diagonal matrix).Link

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