Digital goods generate a large amount of consumer welfare but these welfare gains are not properly measured in existing macroeconomic measures. This chapter summarizes existing research on measuring consumer welfare from digital goods. Recent research suggests that massive online choice experiments could be used to measure welfare gains from digital goods in a scalable manner. These estimates can be used to construct macro-economic welfare measures such as GDP-B that better reflect the reality in the digital economy. However, digital goods need not contribute to improved subjective well-being.
{"title":"Consumer Welfare in the Digital Economy","authors":"A. Collis","doi":"10.2139/ssrn.3733700","DOIUrl":"https://doi.org/10.2139/ssrn.3733700","url":null,"abstract":"Digital goods generate a large amount of consumer welfare but these welfare gains are not properly measured in existing macroeconomic measures. This chapter summarizes existing research on measuring consumer welfare from digital goods. Recent research suggests that massive online choice experiments could be used to measure welfare gains from digital goods in a scalable manner. These estimates can be used to construct macro-economic welfare measures such as GDP-B that better reflect the reality in the digital economy. However, digital goods need not contribute to improved subjective well-being.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"396 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85021837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Giovannelli, Ambra Citton, Cristian Tegami, Tommaso Proietti, O. Ricchi, Cristina Tinti
The national accounts provide a coherent and exaustive description of the current state of the economy, but are available at the quarterly frequency and are released with a nonignorable publication lag. The paper proposes and illustrates a method for nowcasting and forecasting the sixteen main components of Gross Domestic Product (GDP) by output and expenditure type at the monthly frequency, using a high-dimensional set of monthly economic indicators spanning the space of the common macroeconomic and financial factors. The projection on the common space is carried out by combining the individual nowcasts and forecasts arising from all possible bivariate models of the unobserved monthly GDP component and the observed monthly indicator. We discuss several pooling strategies and we select the one showing the best predictive performance according to a pseudo real time forecasting experiment. Monthly GDP can be indirectly estimated by the contemporaneous aggregation of the value added of the different industries and of the expenditure components. This enables the comparative assessment of the indirect nowcasts and forecasts vis-a-vis the direct approach and a growth accounting exercise. Our approach meets the challenges posed by the dimensionality, since it can handle a large number of time series with a complexity that increases linearly with the cross-sectional dimension, while retaining the essential heterogeneity of the information about the macroeconomy. The application to the Italian case leads to several interesting discoveries concerning the time-varying predictive content of the information carried by the monthly indicators.
{"title":"Nowcasting GDP and its Components in a Data-Rich Environment: The Merits of the Indirect Approach","authors":"A. Giovannelli, Ambra Citton, Cristian Tegami, Tommaso Proietti, O. Ricchi, Cristina Tinti","doi":"10.2139/ssrn.3614110","DOIUrl":"https://doi.org/10.2139/ssrn.3614110","url":null,"abstract":"The national accounts provide a coherent and exaustive description of the current state of the economy, but are available at the quarterly frequency and are released with a nonignorable publication lag. The paper proposes and illustrates a method for nowcasting and forecasting the sixteen main components of Gross Domestic Product (GDP) by output and expenditure type at the monthly frequency, using a high-dimensional set of monthly economic indicators spanning the space of the common macroeconomic and financial factors. The projection on the common space is carried out by combining the individual nowcasts and forecasts arising from all possible bivariate models of the unobserved monthly GDP component and the observed monthly indicator. We discuss several pooling strategies and we select the one showing the best predictive performance according to a pseudo real time forecasting experiment. Monthly GDP can be indirectly estimated by the contemporaneous aggregation of the value added of the different industries and of the expenditure components. This enables the comparative assessment of the indirect nowcasts and forecasts vis-a-vis the direct approach and a growth accounting exercise. Our approach meets the challenges posed by the dimensionality, since it can handle a large number of time series with a complexity that increases linearly with the cross-sectional dimension, while retaining the essential heterogeneity of the information about the macroeconomy. The application to the Italian case leads to several interesting discoveries concerning the time-varying predictive content of the information carried by the monthly indicators.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88933172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a short-term forecasting model based on tax data. The model combines daily information from the Immediate Supply of Information System for VAT declaration forms, with monthly indicators derived from tax data. The model uses the GDP as a macroeconomic synthesis. The model combines signal extraction and forecasting at the daily frequency, by means of an unobserved components model, with a mixed frequency (monthly-quarterly) dynamic factor analysis for GDP now-casting and forecasting. The daily information, plus the flexibility and efficiency of the factor models, allows a permanently updated monitoring of the short-term economic conditions of the Spanish economy.
{"title":"Nowcasting the Spanish Economy Using Very High Frequency Tax Data","authors":"Ángel Cuevas, Ramiro Ledo, Enrique M. Quilis","doi":"10.2139/ssrn.3589467","DOIUrl":"https://doi.org/10.2139/ssrn.3589467","url":null,"abstract":"We present a short-term forecasting model based on tax data. The model combines daily information from the Immediate Supply of Information System for VAT declaration forms, with monthly indicators derived from tax data. The model uses the GDP as a macroeconomic synthesis. The model combines signal extraction and forecasting at the daily frequency, by means of an unobserved components model, with a mixed frequency (monthly-quarterly) dynamic factor analysis for GDP now-casting and forecasting. The daily information, plus the flexibility and efficiency of the factor models, allows a permanently updated monitoring of the short-term economic conditions of the Spanish economy.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"193 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77619973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The creation of the National Bureau of Economic Research was a response to the bitter controversies over the distribution of income that roiled the United States during the Progressive Era. Thanks to Malcolm Rorty, a business economist, and Nahum I. Stone, an independent socialist economist, a “Committee on the Distribution of Income” was created; what might be considered the first name of the Bureau. Funding was secured, the Bureau was chartered in 1920, and Wesley Mitchell was appointed the director of research. The Bureau’s first publication, Income in the United States, its Amount and Distribution was widely hailed as a major contribution. Further estimates of national income and its distribution for the 1920s were made by Willford King and Lillian Epstein. The Great Depression led to legislation requiring federal government estimates. Simon Kuznets was seconded from the Bureau to the Commerce Department where he led the team that produced the first federal estimates and established the unit for producing updates. The early investigators at the Bureau proved to be masters of combining sources of data to produce credible estimates. The result was estimates that still underlie our understanding of the growth and fluctuations of the American Economy.
国家经济研究局(National Bureau of Economic Research)的成立是对进步时代困扰美国的关于收入分配的激烈争论的回应。多亏了商业经济学家马尔科姆·罗蒂(Malcolm Rorty)和独立的社会主义经济学家纳胡姆·i·斯通(Nahum I. Stone)，“收入分配委员会”成立了;这可能被认为是该局的名字。资金有了保障，1920年成立了研究局，韦斯利·米切尔被任命为研究部主任。该局的第一份出版物《美国收入、其数额和分配》被广泛认为是一项重大贡献。wilford King和Lillian Epstein进一步估计了20世纪20年代的国民收入及其分配。大萧条导致立法要求联邦政府进行估算。西蒙·库兹涅茨从联邦调查局借调到商务部，在那里他领导的团队制作了第一份联邦预算，并建立了更新部门。事实证明，该局早期的调查人员是综合各种数据来源得出可信估计的高手。其结果是，我们对美国经济增长和波动的理解仍以这些估计为基础。
{"title":"Off to a Good Start: The NBER and the Measurement of National Income","authors":"H. Rockoff","doi":"10.3386/w26895","DOIUrl":"https://doi.org/10.3386/w26895","url":null,"abstract":"The creation of the National Bureau of Economic Research was a response to the bitter controversies over the distribution of income that roiled the United States during the Progressive Era. Thanks to Malcolm Rorty, a business economist, and Nahum I. Stone, an independent socialist economist, a “Committee on the Distribution of Income” was created; what might be considered the first name of the Bureau. Funding was secured, the Bureau was chartered in 1920, and Wesley Mitchell was appointed the director of research. The Bureau’s first publication, Income in the United States, its Amount and Distribution was widely hailed as a major contribution. Further estimates of national income and its distribution for the 1920s were made by Willford King and Lillian Epstein. The Great Depression led to legislation requiring federal government estimates. Simon Kuznets was seconded from the Bureau to the Commerce Department where he led the team that produced the first federal estimates and established the unit for producing updates. The early investigators at the Bureau proved to be masters of combining sources of data to produce credible estimates. The result was estimates that still underlie our understanding of the growth and fluctuations of the American Economy.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"683 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76871884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Brynjolfsson, A. Collis, Erwin Diewert, Felix Eggers, Kevin J. Fox
We suggest a methodology that allows statistical agencies to form approximations to the benefits that flow to households from new free goods. The present production-oriented GDP measures are not satisfactory for measuring real household consumption and will be increasingly inaccurate as free goods, such as those made possible by the digital revolution, become more important. Advertising expenditures are not an adequate substitute for measuring the benefits of new goods to the household sector. Instead, we need to draw on estimates such as those provided by choice experiments.
{"title":"Measuring the Impact of Free Goods on Real Household Consumption","authors":"E. Brynjolfsson, A. Collis, Erwin Diewert, Felix Eggers, Kevin J. Fox","doi":"10.31235/osf.io/gnd4c","DOIUrl":"https://doi.org/10.31235/osf.io/gnd4c","url":null,"abstract":"We suggest a methodology that allows statistical agencies to form approximations to the benefits that flow to households from new free goods. The present production-oriented GDP measures are not satisfactory for measuring real household consumption and will be increasingly inaccurate as free goods, such as those made possible by the digital revolution, become more important. Advertising expenditures are not an adequate substitute for measuring the benefits of new goods to the household sector. Instead, we need to draw on estimates such as those provided by choice experiments.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80778410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the role played by the European Union's Emissions Trading System (EU ETS) as a possible driver of outward foreign direct investment (FDI) for Italian manufacturing firms. Using a panel dataset of about 22,000 firms covering the first two phases of the EU ETS and the period before the EU ETS, we measure the patterns of FDI towards countries not covered by the EU ETS. The results show that the EU ETS had a weak effect on the number of new subsidiaries abroad (extensive margin), while it had a larger impact on production taking place in foreign subsidiaries (intensive margin), especially in trade‐intensive sectors.
{"title":"Outward Foreign Direct Investment Patterns of Italian Firms in the European Union's Emission Trading Scheme","authors":"S. Borghesi, C. Franco, Giovanni Marin","doi":"10.1111/sjoe.12323","DOIUrl":"https://doi.org/10.1111/sjoe.12323","url":null,"abstract":"We consider the role played by the European Union's Emissions Trading System (EU ETS) as a possible driver of outward foreign direct investment (FDI) for Italian manufacturing firms. Using a panel dataset of about 22,000 firms covering the first two phases of the EU ETS and the period before the EU ETS, we measure the patterns of FDI towards countries not covered by the EU ETS. The results show that the EU ETS had a weak effect on the number of new subsidiaries abroad (extensive margin), while it had a larger impact on production taking place in foreign subsidiaries (intensive margin), especially in trade‐intensive sectors.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76691576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate the role of financial factors in the estimation and dynamics of the U.S. output gap over more than a century. We propose a highly parsimonious semi-structural model which produces qualitatively similar dynamics and quantitatively comparable levels and gaps to the U.S. Congressional Budget Office output gap model (Shackleton (2018)). Allowing for time-varying effects of financial factors significantly improves real-time estimates of the output gap. Three major insights follow. Credit dynamics are the primary drivers of the observed financial crisis albeit with different conduits over the century: the stock market in 1929 and the housing market in 2008. Accounting for credit growth, U.S. potential output has been steadily growing at roughly 2% since the beginning of 1980. Long-run TFP levels and dynamics are closely linked to observed variation in potential growth.
{"title":"A Century of Gaps: Where TFP Goes, Potential Follows","authors":"Mihnea Constantinescu, A. Nguyen","doi":"10.2139/ssrn.3503192","DOIUrl":"https://doi.org/10.2139/ssrn.3503192","url":null,"abstract":"We investigate the role of financial factors in the estimation and dynamics of the U.S. output gap over more than a century. We propose a highly parsimonious semi-structural model which produces qualitatively similar dynamics and quantitatively comparable levels and gaps to the U.S. Congressional Budget Office output gap model (Shackleton (2018)). Allowing for time-varying effects of financial factors significantly improves real-time estimates of the output gap. Three major insights follow. Credit dynamics are the primary drivers of the observed financial crisis albeit with different conduits over the century: the stock market in 1929 and the housing market in 2008. Accounting for credit growth, U.S. potential output has been steadily growing at roughly 2% since the beginning of 1980. Long-run TFP levels and dynamics are closely linked to observed variation in potential growth.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85057923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Este documento estima el valor del producto interno bruto, PIB, de la produccion de cocaina y, en particular, el valor agregado por la base de coca y por el clorhidrato de cocaina. Este valor del PIB de la cocaina es muy sensible a los precios y cantidades de insumos y de productos en diferentes puntos de la geografia del pais. Los precios del clorhidrato de cocaina se incrementan exponencialmente desde los datos observados en los laboratorios en el interior del pais, hasta llegar a los puertos de exportacion y a los mercados de consumo. Los datos aqui utilizados fueron tomados de la informacion del Sistema Integrado de Monitoreo de Cultivos Ilicitos, SIMCI, de la Oficina de las Naciones Unidas Contra la Droga y el Delito, UNODC. Si se asume un precio FOB del clorhidrato de cocaina igual al precio de frontera fisica mas un 10% del diferencial entre el precio mayorista en los EEUU y dicho precio de frontera, el PIB de la cocaina alcanzaria un 1,88% del PIB total en 2018, mas de dos veces el PIB de un sector emblematico como el cafe, que representa un 0,8% del PIB. Dicha cifra es igualmente preocupante comparada con la del periodo 2011-14, cuando en promedio solo represento un 0,6% del PIB, y en terminos nominales alcanzo en 2018 unos $18 billones. El valor agregado de la cocaina calculado solo con el precio estimado en puerto de salida, que habia caido en promedio a un 0,42% del PIB nacional hacia 2011-14, volvio a crecer hasta alcanzar un nivel de 0,88% del PIB total en 2017 y 1,06% en 2018. Dicha expansion esta fundamentalmente explicada por el crecimiento de las siembras de la mata de coca, la cual alcanzo en 2017 las 171 mil hectareas niveles superiores a los del ano 2000 que se situaron cerca de 163 mil hectareas y en 2018 cerca de 169 mil hectareas. Debido a una politica estricta de erradicacion, ese nivel habia caido a menos de 50,000 hectareas en 2010.
{"title":"El PIB de la Cocaína 2005-2018: Una Estimación empírica (Cocaine GDP 2005-2018: An Empirical Estimate)","authors":"S. Montenegro, Jorge Llano, D. Ibanez","doi":"10.2139/ssrn.3499830","DOIUrl":"https://doi.org/10.2139/ssrn.3499830","url":null,"abstract":"Este documento estima el valor del producto interno bruto, PIB, de la produccion de cocaina y, en particular, el valor agregado por la base de coca y por el clorhidrato de cocaina. Este valor del PIB de la cocaina es muy sensible a los precios y cantidades de insumos y de productos en diferentes puntos de la geografia del pais. Los precios del clorhidrato de cocaina se incrementan exponencialmente desde los datos observados en los laboratorios en el interior del pais, hasta llegar a los puertos de exportacion y a los mercados de consumo. Los datos aqui utilizados fueron tomados de la informacion del Sistema Integrado de Monitoreo de Cultivos Ilicitos, SIMCI, de la Oficina de las Naciones Unidas Contra la Droga y el Delito, UNODC. Si se asume un precio FOB del clorhidrato de cocaina igual al precio de frontera fisica mas un 10% del diferencial entre el precio mayorista en los EEUU y dicho precio de frontera, el PIB de la cocaina alcanzaria un 1,88% del PIB total en 2018, mas de dos veces el PIB de un sector emblematico como el cafe, que representa un 0,8% del PIB. Dicha cifra es igualmente preocupante comparada con la del periodo 2011-14, cuando en promedio solo represento un 0,6% del PIB, y en terminos nominales alcanzo en 2018 unos $18 billones. El valor agregado de la cocaina calculado solo con el precio estimado en puerto de salida, que habia caido en promedio a un 0,42% del PIB nacional hacia 2011-14, volvio a crecer hasta alcanzar un nivel de 0,88% del PIB total en 2017 y 1,06% en 2018. Dicha expansion esta fundamentalmente explicada por el crecimiento de las siembras de la mata de coca, la cual alcanzo en 2017 las 171 mil hectareas niveles superiores a los del ano 2000 que se situaron cerca de 163 mil hectareas y en 2018 cerca de 169 mil hectareas. Debido a una politica estricta de erradicacion, ese nivel habia caido a menos de 50,000 hectareas en 2010.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75191028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a new measure of the output gap based on a dynamic factor model that is estimated on a large number of U.S. macroeconomic indicators and which incorporates relevant stylized facts about macroeconomic data (co-movements, non-stationarity, and the slow drift in long-run output growth over time). We find that, (1) from the mid-1990s to 2008, the U.S. economy operated above its potential; and, (2) in 2018:Q4, the labor market was tighter than the market for goods and services. Because it is mainly data-driven, our measure is a natural complementary tool to the theoretical models used at policy institutions.
{"title":"Measuring the Output Gap Using Large Datasets","authors":"M. Barigozzi, Matteo Luciani","doi":"10.2139/ssrn.3217816","DOIUrl":"https://doi.org/10.2139/ssrn.3217816","url":null,"abstract":"\u0000 We propose a new measure of the output gap based on a dynamic factor model that is estimated on a large number of U.S. macroeconomic indicators and which incorporates relevant stylized facts about macroeconomic data (co-movements, non-stationarity, and the slow drift in long-run output growth over time). We find that, (1) from the mid-1990s to 2008, the U.S. economy operated above its potential; and, (2) in 2018:Q4, the labor market was tighter than the market for goods and services. Because it is mainly data-driven, our measure is a natural complementary tool to the theoretical models used at policy institutions.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"198 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74212278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The official statistics – whether the published aggregates or the confidential microdata – do not support the longstanding view that US direct investment abroad (USDIA) outperforms foreign direct investment in the US (FDIUS). Rather, the apparent yields differential results primarily from two subtleties of the data. First, USDIA business activity is "double counted" at holding companies. Second, unlike FDIUS, USDIA profits are not recorded on a fully after-tax basis. Leading explanations for the relative profitability of USDIA, such as income shifting and industry composition, have limited or countervailing effects. The US does not enjoy an exorbitant privilege in direct investment returns.
{"title":"The Direct Investment Income Puzzle","authors":"James F. Albertus","doi":"10.2139/ssrn.3248774","DOIUrl":"https://doi.org/10.2139/ssrn.3248774","url":null,"abstract":"The official statistics – whether the published aggregates or the confidential microdata – do not support the longstanding view that US direct investment abroad (USDIA) outperforms foreign direct investment in the US (FDIUS). Rather, the apparent yields differential results primarily from two subtleties of the data. First, USDIA business activity is \"double counted\" at holding companies. Second, unlike FDIUS, USDIA profits are not recorded on a fully after-tax basis. Leading explanations for the relative profitability of USDIA, such as income shifting and industry composition, have limited or countervailing effects. The US does not enjoy an exorbitant privilege in direct investment returns.","PeriodicalId":18164,"journal":{"name":"Macroeconomics: National Income & Product Accounts eJournal","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89942670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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