Taking the Pulse of the Economy: Measuring GDP

Landefeld, J. Steven; Seskin, Eugene P.; Fraumeni, Barbara M.

doi:10.1257/jep.22.2.193

Cited by 166 publications

(108 citation statements)

References 5 publications

(1 reference statement)

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“…Current economic development studies have already pointed out certain factors influencing the GDP, including energy consumption, foreign direct investment and CO 2 emissions [26]. In addition, some parameters that contribute to the GDP, such as retail sales, service sector and manufacturers' shipments, are hard to measure [27]. Therefore, the use of the remote sensing technique to model the GDP only contributes to a certain degree (in a particular spatial dimension), while other socio-economic and environmental factors should be considered in order to derive a more universal indicator to predict the economic development at the country-wide level.…”

Section: Regression Analysis Between the Socio-economic Parameters Anmentioning

confidence: 99%

Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Faisal

Shaker

Habbani³

2016

IJGI

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City/regional authorities are responsible for designing and structuring the urban morphology based on the desired land use activities. One of the key concerns regarding urban planning is to establish certain development goals, such as the real gross domestic product (GDP). In Canada, the gross national income (GNI) mainly relies on the mining and manufacturing industries. In order to estimate the impact of city development, this study aims to utilize remote sensing and Geographic Information System (GIS) techniques to assess the relationship between the built-up area and the reported real GDP of seven major cities in Canada. The objectives of the study are: (1) to investigate the use of regression analysis between the built-up area derived from Landsat images and the industrial area extracted from Geographic Information System (GIS) data; and (2) to study the relationship between the built-up area and the socio-economic data (i.e., real GDP, total population and total employment). The experimental data include 42 multi-temporal Landsat TM images and 42 land use GIS vector datasets obtained from year 2005 to 2010 during the summer season (June, July and August) for seven major cities in Canada. The socio-economic data, including the real GDP, the total population and the total employment, are obtained from the Metropolitan Housing Outlook during the same period. Both the Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) were used to determine the built-up areas. Those high built-up values within the industrial areas were acquired for further analysis. Finally, regression analysis was conducted between the real GDP, the total population, and the total employment with respect to the built-up area. Preliminary findings showed a strong linear relationship (R 2 = 0.82) between the percentage of built-up area and industrial area within the corresponding city. In addition, a strong linear relationship (R 2 = 0.8) was found between the built-up area and socio-economic data. Therefore, the study justifies the use of remote sensing and GIS data to model the socio-economic data (i.e., real GDP, total population and total employment). The research findings can contribute to the federal/municipal authorities and act as a generic indicator for targeting a specific real GDP with respect to industrial areas.

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Section: Regression Analysis Between the Socio-economic Parameters Anmentioning

confidence: 99%

Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Faisal

Shaker

Habbani³

2016

IJGI

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“…Our inferences are unchanged using aggregate series based on cross-sectional sums. 5 We focus on the advance realization of GDP growth because NIPA revisions tend to be small and most of the information about the state of the economy is known over the period leading to the BEA's advance NIPA report (Fixler and Grimm 2005;Lahiri and Wang 2006;Landefeld, Seskin, and Fraumeni 2008). The advance and final realizations of GDP growth have a correlation coefficient of 0.96 and our inferences are not sensitive to this choice.…”

Section: Figure 3 Aggregate Changes In Accounting Profitabilitymentioning

confidence: 99%

Taking the Pulse of the Real Economy Using Financial Statement Analysis: Implications for Macro Forecasting and Stock Valuation

Konchitchki

Patatoukas²

2013

SSRN Journal

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In this study, we hypothesize and find that financial statement analysis of firm profitability drivers applied at the aggregate level yields timely insights that are relevant for forecasting real economic activity. We first show that focusing on the 100 largest firms offers a cost-effective way to extract information embedded in accounting profitability data of the entire stock market portfolio. We then show that accounting profitability data aggregated across the 100 largest firms have predictive content for subsequent real Gross Domestic Product (GDP) growth. We also show that stock market returns have predictive content for future real GDP growth, while their predictive power varies with the length of the measurement window with annual stock market returns being the most powerful. Importantly, we find that the predictive content of our indices of aggregate accounting profitability drivers is incremental to that of annual stock market returns. An in-depth investigation of consensus survey forecasts shows that professional macro forecasters revise their expectations of real economic activity in the direction of the predictive content of aggregate accounting profitability drivers and stock market returns. Although macro forecasters are fully attuned to stock market return data, their forecasts of real GDP growth can be improved in a statistically and economically significant way using our indices of aggregate accounting profitability drivers. Our findings suggest that professional macro forecasters and stock market investors do not fully impound the predictive content of aggregate accounting profitability drivers when forecasting real economic activity. In additional analysis, we examine the association between stock market returns and the portion of subsequent real GDP growth that is predictable based on our indices of aggregate accounting profitability drivers but that is not anticipated by stock market investors. We find that this portion is positively related to stock market returns, suggesting that the macro predictive content of aggregate accounting profitability drivers is relevant for stock valuation. Overall, our study bringsWe thank John Harry Evans III (senior editor), Kenneth A. Merchant (editor), and two anonymous reviewers for their comments and suggestions. We also thank Severin Borenstein, Sunil Dutta, Reut Laufer, Topseht Nonam, George Patatoukas, Mary Psyllaki, Andy Rose, and seminar participants at the University of California, Berkeley for helpful comments and suggestions. We gratefully acknowledge financial support from the Hellman Fellows Program and the Center for Financial Reporting and Management at the University of California, Berkeley, Haas School of Business.Editor's note: Accepted by Kenneth A. Merchant. Submitted: April 2012Accepted: July 2013 Published Online: October 2013 669 financial statement analysis to the forefront as an incrementally useful tool for gauging the prospects of the real economy that should be of interest to academics and practitioners.

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“…These adjustments are meant to generate an accrual accounting based estimate of aggregate corporate profits that is consistent with the BEA's notion of economic income, free from changes in GAAP and tax laws, and consistent across time (BEA 2004, BEA 2007a, Landefeld et al 2008. Two of the most significant adjustments are the inventory valuation and capital consumption adjustments.…”

Section: Aggregate Corporate Profitsmentioning

confidence: 99%

“…The chained approach is computationally difficult, and the level of an index in any single period is not in itself meaningful. However, the relation of an index level to an index level in another period can be used to create inflation-adjusted aggregate measures (BEA 2008, Landefeld et al 2008 …”

Section: Adjustments For Price Level Changesmentioning

confidence: 99%

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Macroeconomic Consequences of Accounting: The Effect of Accounting Conservatism on Macroeconomic Indicators and the Money Supply

Crawley

2014

The Accounting Review

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This study investigates the macroeconomic consequences of firm-level accounting conservatism. Consistent with conditional conservatism extending to the aggregate level, I demonstrate that annual estimates of aggregate corporate profits and gross domestic product compiled by the U.S. Bureau of Economic Analysis are more sensitive to negative aggregate news than to positive aggregate news. Next, I estimate the dollar value impact of conservatism on measurements of macroeconomic fundamentals. Finally, I show that incorporating the dollar value impact of conservatism increases the explanatory power of a monetary policy reaction function that describes U.S. Federal Reserve interest rate decision behavior. These results suggest that accounting can impact social welfare by altering the measurement attributes of key macroeconomic indicators and by shaping monetary policy decisions that regulate the money supply. JEL Classifications: M41; E43; E52.

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Taking the Pulse of the Economy: Measuring GDP

Cited by 166 publications

References 5 publications

Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Taking the Pulse of the Real Economy Using Financial Statement Analysis: Implications for Macro Forecasting and Stock Valuation

Macroeconomic Consequences of Accounting: The Effect of Accounting Conservatism on Macroeconomic Indicators and the Money Supply

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