Providing high-quality economic forecasts is an important responsibility of the International Monetary Fund(IMF) in maintaining world financial and economic stability. However, errors are inevitable in IMF economic fo...Providing high-quality economic forecasts is an important responsibility of the International Monetary Fund(IMF) in maintaining world financial and economic stability. However, errors are inevitable in IMF economic forecasts for its member countries. Based on forecast method and information, and political factor, this paper creates a political economics framework for analyzing the IMF's forecast errors, and tests the effects of various factors on the IMF's forecasts using the panel data analysis method. According to our findings, if a country receives IMF loans and shares a similar vote with the United States at the UN General Assembly, it will more likely receive an optimistic forecast by the IMF. Meanwhile, member countries' data availability and IMF forecast errors for major economies may also affect forecast on a country. Therefore, this paper proposes recommendations on further improving the IMF's forecast quality by creating more independent forecast procedures and enhancing forecast data quality and forecast accuracy.展开更多
International economic statistics play central roles in global economic governance.Governments and international organizations rely on them to monitor international economic agreements;governments use them to understa...International economic statistics play central roles in global economic governance.Governments and international organizations rely on them to monitor international economic agreements;governments use them to understand potential imbalances in bilateral relationships;and international investors build their country assessments on such data.These statistics increasingly suffer from serious defects,however,due to globalization,the digitization of our economies,and the prominence of secrecy jurisdictions and multinational corporations.For that reason,economic data is not a neutral arbiter in international affairs.Instead,it suffers from four kinds of bias:Expert attention bias means that the objects of measurement-what they are meant to capture-epend on the preoccupations of the small circle of statistical experts.Countability bias skews economic figures in favor of countable objects and away from,fbr example,unremunerated labor and production as well as ephemeral economic process,such as knowledge production.Capitalist bias emerges because economic statistics naturalize unequal power relations in the global economy:They mistake a country's inability to fetch high prices for its products for low productivity and a lack of added value.Stealth-wealth bias,finally,means that statistics naturalize the distorted image we have of the global economy as corporations and individual hide profits and wealth in secrecy jurisdictions.This article cautions against an insufficiently critical use of statistics in international affairs.And it encourages policymakers to"know thy data"lest biases in the numbers generate skewed policies,unnecessary disputes and a gradual delegitimization of statistics in general.展开更多
文摘Providing high-quality economic forecasts is an important responsibility of the International Monetary Fund(IMF) in maintaining world financial and economic stability. However, errors are inevitable in IMF economic forecasts for its member countries. Based on forecast method and information, and political factor, this paper creates a political economics framework for analyzing the IMF's forecast errors, and tests the effects of various factors on the IMF's forecasts using the panel data analysis method. According to our findings, if a country receives IMF loans and shares a similar vote with the United States at the UN General Assembly, it will more likely receive an optimistic forecast by the IMF. Meanwhile, member countries' data availability and IMF forecast errors for major economies may also affect forecast on a country. Therefore, this paper proposes recommendations on further improving the IMF's forecast quality by creating more independent forecast procedures and enhancing forecast data quality and forecast accuracy.
基金This research has been supported by the European Research Council Starting Grant FICKLEFORMS(Grant#637883)the Netherlands Organisation for Scientific Research NWO Vidi project 016.145.395.
文摘International economic statistics play central roles in global economic governance.Governments and international organizations rely on them to monitor international economic agreements;governments use them to understand potential imbalances in bilateral relationships;and international investors build their country assessments on such data.These statistics increasingly suffer from serious defects,however,due to globalization,the digitization of our economies,and the prominence of secrecy jurisdictions and multinational corporations.For that reason,economic data is not a neutral arbiter in international affairs.Instead,it suffers from four kinds of bias:Expert attention bias means that the objects of measurement-what they are meant to capture-epend on the preoccupations of the small circle of statistical experts.Countability bias skews economic figures in favor of countable objects and away from,fbr example,unremunerated labor and production as well as ephemeral economic process,such as knowledge production.Capitalist bias emerges because economic statistics naturalize unequal power relations in the global economy:They mistake a country's inability to fetch high prices for its products for low productivity and a lack of added value.Stealth-wealth bias,finally,means that statistics naturalize the distorted image we have of the global economy as corporations and individual hide profits and wealth in secrecy jurisdictions.This article cautions against an insufficiently critical use of statistics in international affairs.And it encourages policymakers to"know thy data"lest biases in the numbers generate skewed policies,unnecessary disputes and a gradual delegitimization of statistics in general.
