Quantitative indicators at the local level play an increasingly important role in the formulation and evaluation of regional policies. Regional statistical indicators are available from several sources, but comparability of their time-series is often affected by breaks caused by boundary changes...

Quantitative indicators at the local level play an increasingly important role in the formulation and evaluation of regional policies. Regional statistical indicators are available from several sources, but comparability of their time-series is often affected by breaks caused by boundary changes...

Wer langfristig am Markt bestehen will, kommt am Thema Daten nicht vorbei. Richtig ist aber auch, dass nicht jedes Unternehmen die gleichen Datenpotenziale einlösen kann. Die hohe Erwartungshaltung, was das Potenzial der Daten angeht, wird stark durch den Erfolg weniger Konzerne bestimmt, den...

High-quality company data is crucial for state-of-the-art empirical research and competition, as well as for evidence-based policy advice, reliable forecasts and policy evaluations. In Germany, however, there are striking deficits in the availability of and access to company data compared to...

This study examines the impact of access to confidential administrative data on the rate, direction, and policy relevance of economics research. To study this question, we exploit the progressive geographic expansion of the U.S. Census Bureau's Federal Statistical Research Data Centers (FSRDCs)....

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

When the COVID-19 pandemic began in early 2020, the amount of telework sharply increased, allowing people to work while limiting their exposure to others. At that time, there were no regular monthly economic indicators measuring the prevalence of telework. Thus, the U.S. Bureau of Labor...

The Global Macro Database is an open-source, continuously updated dataset of macroeconomic statistics that unifies and extends existing resources. By harmonizing and integrating data from 32 major contemporary sources--including the IMF, World Bank, and OECD--with historical records from 78...

We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This results in an increase in total social welfare, and a transfer of surplus from...

As financial technology improves and data becomes more abundant, do market prices reflect this data growth? While recent studies documented rises in the information content of prices, we show that, across asset types, there is data divergence. Large, growth stock prices increasingly reflect...

We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This increases total social welfare, and transfers surplus from borrowers to lenders. We...

We introduce FDIF, a measure of Fed communication surprise based on the text of FOMC statements. FDIF measures the difference between text-implied and actual values of key market variables. Positive FDIF of countercyclical variables (e.g., credit spreads) is associated with negative...

Machine learning have made a large number of novel applications in various domains in finance. Though more complex and advanced models have been proposed and explored in literatures, the input data to the models and how the raw features are preprocessed, remains important. This article provides...

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others' characteristics. It can...

The use of historical data has become a standard tool in economics, serving three main purposes: to examine the influence of the past on current economic outcomes; to use unique natural experiments to test modern economic theories; and to use modern economic theories to refine our understanding...

The Mannheim European panel on Financial Indicators and Emissions (ME-FINE) is a new European company-level dataset, combining financial information from Bureau van Dijk's Orbis database with data on pollutant emissions from the European Pollutant Emission Register (EPER) and its successor, the...

The Census Bureau's Longitudinal Business Database (LBD) underpins many studies of firm-level behavior. It tracks longitudinally all employers in the nonfarm private sector but lacks information about business financing and owner characteristics. We address this shortcoming by linking LBD...

We test and compare the effects of introduction of two new financial information technologies, EDGAR and XBRL, on well-known asset pricing anomalies often attributed to mispricing. EDGAR facilitates easier access to public accounting information about public firms; XBRL reduces the cost of...

Dun's Review began publishing monthly data on bankruptcies by branch of business during the 1890s. Those series evolved through many iterations. This essay reconstructs the series from 1895 to 1935 and discusses how it can be used for economic analysis

National surveys are crucial for estimating key economic aggregates, including the unemployment rate, labor force participation, and household expenditures. The accuracy of these indicators is increasingly under scrutiny due to declining response rates and the consequent risk of nonresponse...

In this article, we present and describe FRED-QD, a large, quarterly frequency macroeconomic database that is currently available and regularly updated at https://research.stlouisfed.org/econ/mccracken/fred-databases/. The data provided are closely modeled to that used in Stock and Watson...

We analyse the use of current and forward-looking data in the setting of monetary policy (Taylor rule). We answer the question of whether the use of forward-looking data is to be preferred over the use of current data. We use a behavioural macroeconomic model that generates periods of...

Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and...

Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy...

The rise of information technology and big data analytics has given rise to "the new economy." But are its economics new? This article constructs a growth model where firms accumulate data, instead of capital. We incorporate three key features of data: 1) Data is a by-product of economic...

The use of historical data has become a standard tool in economics, serving three main purposes: to examine the influence of the past on current economic outcomes; to use unique natural experiments to test modern economic theories; and to use modern economic theories to refine our understanding...

This paper provides a documentation of the ifo Prussian Economic History Database (iPEHD), a county-level database covering a rich collection of variables for 19th-century Prussia. The Royal Prussian Statistical Office collected these data in several censuses over the years 1816-1901, with much...

This paper focuses on the importance data issues to the analysis of growth, poverty and economic inequality. We introduce a number of major databases frequently used in applied research on growth, poverty and global and international inequality. A discussion of data quality, data consistency,...

In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data”...

In the first chapter, we reconsider the idea of trend-based predictability using methods that flexibly learn price patterns that are most predictive of future returns, rather than testing hypothesized or pre-specified patterns (e.g., momentum and reversal). Our raw predictor data are...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

The amount of information produced about firms' productivities and about the quality of collateral backing their loans varies over time. These information dynamics determine the evolution of credit, output and productivity, which feeds back into incentives to produce information. We characterize...