A High-frequency Monthly Measure of Real Economic Activity in Pakistan

Mahmood, Asif and Masood, Hina (2024): A High-frequency Monthly Measure of Real Economic Activity in Pakistan.

Abstract

Evaluating the current state of the business cycle is of crucial importance to policymakers for making effective decisions. However, economic data are often noisy and available with a substantial lag. Determining the underlying state of an economy is thus very difficult in practice as traditional national accounts data are often available on quarterly or annual basis. To overcome these gaps, policymakers, especially at the central banks, started to closely track the changes in high-frequency economic activity indicators. In this paper, learning from global best practices, we attempt to develop a composite monthly measure of real economic activity for Pakistan using available high-frequency data. Our constructed measure closely tracks the trend in the real GDP, which is available with relatively large lags from Pakistan Bureau of Statistics. Provided this important characteristic, we test and found a reasonable power of our monthly measure to nowcast real GDP growth for a reference quarter.

• Item Type: MPRA Paper
• Language: English
• Keywords: Economic Activity, High-frequency data, GDP
• Subjects: E - Macroeconomics and Monetary Economics > E0 - General > E01 - Measurement and Data on National Income and Product Accounts and Wealth ; Environmental Accounts; E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E23 - Production

References

Armesto, M.T., Engemann, K.M. and Owyang, M.T., 2010. Forecasting with mixed frequencies. Federal Reserve Bank of St. Louis Review, 92(6), pp.521-536.

Aruoba, S.B. and Sarikaya, C., 2013. A real economic activity indicator for Turkey. Central Bank Review, 13(1), p.15.

Aruoba, S.B., Diebold, F.X. and Scotti, C., 2009. Real-time measurement of business conditions. Journal of Business & Economic Statistics, 27(4), pp.417-427.

Baffigi, A., Golinelli, R. and Parigi, G., 2004. Bridge models to forecast the euro area GDP. International Journal of Forecasting, 20(3), pp.447-460.

Bragoli, D. and Fosten, J., 2018. Nowcasting indian gdp. Oxford Bulletin of Economics and Statistics, 80(2), pp.259-282.

Burns, A.F. and Mitchell, W.C., 1946. Measuring business cycles. National Bureau of Economic Research.

Crawley, M.J., 2012. The R book. John Wiley & Sons.

Dahlhaus, T., Guénette, J.D. and Vasishtha, G., 2017. Nowcasting BRIC+ M in real time. International Journal of Forecasting, 33(4), pp.915-935.

Foroni, C., Marcellino, M. and Schumacher, C., 2015. Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials. Journal of the Royal Statistical Society Series A: Statistics in Society, 178(1), pp.57-82.

Geweke, J., 1977. The dynamic factor analysis of economic time series. Latent variables in socio-economic models.

Ghysels, E., Santa-Clara, P. and Valkanov, R., 2004. The MIDAS touch: Mixed data sampling regression models.

Giannone, D., Reichlin, L. and Small, D., 2008. Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, 55(4), pp.665-676.

Lewis, D.J., Mertens, K., Stock, J.H. and Trivedi, M., 2022. Measuring real activity using a weekly economic index. Journal of Applied Econometrics, 37(4), pp.667-687.

Mariano, R.S. and Murasawa, Y., 2003. A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics, 18(4), pp.427-443.

Proietti, T. and Moauro, F., 2006. Dynamic factor analysis with non-linear temporal aggregation constraints. Journal of the Royal Statistical Society Series C: Applied Statistics, 55(2), pp.281-300.

Sampi, J. and Jooste, C., 2020. Nowcasting Economic Activity in Times of COVID-19. Policy Research Working Paper, 9247.

Sargent, T.J. and Sims, C.A., 1977. Business cycle modeling without pretending to have too much a priori economic theory. New methods in business cycle research, 1, pp.145-168.

Stanger, M.M., 2020. A Monthly Indicator of Economic Growth for Low Income Countries. International Monetary Fund.

State Bank of Pakistan, 2023. The state of Pakistan's economy. Annual Report 2022-23. State Bank of Pakistan.

Stock, J.H. and Watson, M.W., 1989. New indexes of coincident and leading economic indicators. NBER Macroeconomics Annual, 4, pp.351-394.