The role of accounting information in forecasting Gross domestic product

Document Type : Original Article

Authors
1 Ph.D Candidate, Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
2 Assistant Professor, Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
3 Assistant Professor, Department of Economics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
4 Assistant Professor, Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
Abstract
Gross domestic product (GDP) is one of the key indicators of macroeconomics. Predicting this index is very important in the economic planning of the country, because this variable reflects the general state of a country's economy. So far, many models have been proposed to predict this variable, but models that use accounting information have not been considered. The purpose of this paper is to examine the relationship between GDP and total corporate profits, as one of the known variables in accounting. For this purpose, the quarterly time series data of macro level companies of Tehran Stock Exchange and macroeconomics in the period 2009 to 2018 are analyzed in two stages. In the first step, the relationship between these two variables is determined by specifying a linear regression model that will be estimated using the least squares method. To evaluate the predictive power of this model, the root mean square error (RMSE) criterion is estimated in two scenarios with total corporate profit and no corporate total profit. Second, the GDP response to the shock to firms' profits is estimated through a vector auto regression (VAR) model, and the contribution of this variable to GDP fluctuation is measured. The results show that the profit of all companies improves GDP forecast in the leading horizons. Also, the shock to the profits of all companies, as much as a standard deviation, explains about 28% of GDP fluctuations.
Keywords

  • برکچیان، سید مهدی؛ سمائی، کیان. (1399). ارزیابی نشانگرهای پیشرو برای تولید ناخالص داخلی ایران. مطالعات اقتصادی کاربردی ایران. شماره 34; از صفحه 1 تا 37.
  • خواجوی، شکراله؛ نجفی، زهرا. (1394). آزمون محدودیت­های حاکم بر ویژگی­های کیفی اطلاعات حسابداری. بررسی­های حسابداری و حسابرسی. دوره 22 , شماره 4 ; از صفحه 421 تا 440.
  • نقدی، سجاد.، اسدی،غلامحسین.، فضل زاده، علیرضا. (1396). از حسابداری به اقتصاد: نگرشی نوین در تأیید اهمیت اطلاعات حسابداری مالی. پیشرفت­های حسابداری دوره نهم پاییز و زمستان شماره 2 .
  • گجراتی،  دامودار(بی تا)، مبانی اقتصاد سنجی. ترجمه ابریشمی، حمید.(1390).موسسه چاپ و انتشارات دانشگاه تهران
  • Abdalla, A., & Carabias, J. M. (2017). From accounting to economics: the role of aggregate special items in gauging the state of the economy. Available at SSRN 2871600.
  • Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth?. Journal of econometrics, 131(1-2), 359-403.
  • Ball, R., Sadka, G., & Sadka, R. (2009). Aggregate earnings and asset prices. Journal of Accounting Research, 47(5), 1097-1133.
  • Dechow, P. M., Kothari, S. P., & Watts, R. L. (1998). The relation between earnings and cash flows. Journal of accounting and Economics, 25(2), 133-168.
  • Gaertner, F. B., Kausar, A., & Steele, L. B. (2020). Negative accounting earnings and gross domestic product. Review of Accounting Studies, 25(4), 1382-1409.
  • Fischer, S., & Merton, R. C. (1984). Macroeconomics and finance: The role of the stock market (No. w1291). National Bureau of Economic Research.
  • Gaertner, F. B., Kausar, A., & Steele, L. B. (2017). The usefulness of negative aggregate earnings changes in predicting future gross domestic product growth. Available at SSRN 2656597.
  • Gallo, L. A., Hann, R. N., & Li, C. (2016). Aggregate earnings surprises, monetary policy, and stock returns. Journal of Accounting and Economics, 62(1), 103-120.
  • Ghajar, E., & Saeidi, P. (2016). Investigating the Relationship between Accounting earning and Gross Domestic Product in Companies Listed in Tehran Stock Exchange. Advances in Mathematical Finance and Applications, 1(1), 57-66.
  • Fama, E. F. (1981). Stock returns, real activity, inflation, and money. The American economic review, 71(4), 545-565.
  • Harvey, C. R. (1989). Forecasts of economic growth from the bond and stock markets. Financial Analysts Journal, 45(5), 38-45.
  • Henderson, J. V., Storeygard, A., & Weil, D. N. (2012). Measuring economic growth from outer space. American economic review, 102(2), 994-1028.
  • Kalay, A., Nallareddy, S., & Sadka, G. (2018). Uncertainty and sectoral shifts: The interaction between firm-level and aggregate-level shocks, and macroeconomic activity. Management Science, 64(1), 198-214
  • Konchitchki, Y. (2011). Inflation and nominal financial reporting: Implications for performance and stock prices. The Accounting Review, 86(3), 1045-1085.
  • Konchitchki, Y., & Patatoukas, P. N. (2014). Taking the pulse of the real economy using financial statement analysis: Implications for macro forecasting and stock valuation. The Accounting Review, 89(2), 669-694.
  • Konchitchki, Y., & Patatoukas, P. N. (2014b). Accounting earnings and gross domestic product. Journal of Accounting and Economics, 57(1), 76-88.
  • Konchitchki, Y., & Patatoukas, P. N. (2014a). Taking the pulse of the real economy using financial statement analysis: Implications for macro forecasting and stock valuation. The Accounting Review, 89(2), 669-694.
  • Kothari, S. P., Shivakumar, L., & Urcan, O. (2013). Aggregate earnings surprises and inflation forecasts. Unpublished Paper, MIT Sloan School of Management and London Business School.
  • Li, N., Richardson, S., & Tuna, İ. (2014). Macro to micro: Country exposures, firm fundamentals and stock returns. Journal of Accounting and Economics, 58(1), 1-20.
  • Lalwani, V., & Chakraborty, M. (2020`). Aggregate earnings and gross domestic product: International evidence. Applied Economics, 52(1), 68-84.
  • Nagdi, S., Assadi, G., & Fazllzadeh, A. (2017). From Accounting to Economics: A New Approach in Recognition of the Importance of Financial Accounting Information.
  • Naghdi, S., Assadi, G., Fazlzadeh, A., & Noferesti, M. (2018). Macro-economic Modeling and Forecasting using aggregate Earnings and Management Earnings Forecasts. Empirical Research in Accounting, 7(4), 165-190.
  • Naghdi, S. (2018). Designing and formulating the forecasting model of economic growth by accounting approach. Journal of Accounting of Knowledge, 9(3), 39-63.
  • Nallareddy, S., & Ogneva, M. (2017). Predicting restatements in macroeconomic indicators using accounting information. The Accounting Review, 92(2), 151-182.
  • Odoemelam, N., Ofoegbu, N. G., & Okafor, G. R. (2019). Aggregate Earnings and (Un) employment Rate: Evidence from Nigeria. Asian Journal of Economics, Business and Accounting, 1-19.
  • Rouxelin, F., Wongsunwai, W., & Yehuda, N. (2018). Aggregate cost stickiness in GAAP financial statements and future unemployment rate. The Accounting Review, 93(3), 299-325.
  • Salehi, M., Gah, A. D., Akbari, F., & Naghshbandi, N. (2020). Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran. International Journal of Organizational Analysis.
  • Stark, T. (2010). Realistic evaluation of real-time forecasts in the Survey of Professional Forecasters. Federal Reserve Bank of Philadelphia Research Rap, Special Report, 1.
  • Stock, J. H., & Watson, M. W. (2003). How did leading indicator forecasts perform during the 2001 recession?. FRB Richmond Economic Quarterly, 89(3), 71-90.
  • Zarnowitz, V., & Braun, P. (1993). Twenty-two years of the NBER-ASA quarterly economic outlook surveys: aspects and comparisons of forecasting performance. In Business cycles, indicators, and forecasting (pp. 11-94). University of Chicago Press.