The role of aggregate cost stickiness in unemployment rate prediction

الموضوعات :

Naser Riyahinasab ¹ (Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.)
Babak Jamshidinavid ² (Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.)
Alireza Moradi ³ (Department of Economics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.)
Mehrdad Ghanbari ⁴ (Department of Accounting, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.)

تاريخ الإرسال : 24 الأحد , جمادى الأولى, 1441 تاريخ التأكيد : 01 الإثنين , ذو القعدة, 1441 تاريخ الإصدار : 28 السبت , جمادى الأولى, 1443

الکلمات المفتاحية: VAR model, Unemployment Rate, aggregate cost stickiness, forecast error,

ملخص المقالة :

Predicting macroeconomic indicators is very important for policymakers and economists. Unemployment is one of the key indicators of macroeconomics that has adverse economic and social consequences. So far, many models have been proposed to predict this variable, but models in which accounting information was used to predict unemployment rate were ignored. The purpose of this paper is to investigate the relationship between aggregate cost stickiness, as one of the known variables in accounting, and unemployment rate. To this end, seasonal macro level time series data of Tehran Stock Exchange (TSE) and macroeconomic data are analyzed in two stages from 2008:2 to 2018:1. In the first stage, the relationship between these two variables is determined by specifying a linear regression model that is estimated using the OLS method. To investigate the predictive power of this model, the RMSE criterion was estimated in two scenarios with and without aggregate cost stickiness. Secondly, the reaction of the unemployment rate in response to a shock from aggregate cost stickiness is estimated by a Vector Autoregressive (VAR) model and the share of this variable is measured in the fluctuations of unemployment rate. The results show that aggregate cost stickiness improves the forecast of unemployment rate in the horizon previous. Also, the shock of aggregate cost stickiness explains about 6.5 percent of unemployment rate fluctuations.

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