Abstract:
This studyexamines the role of internal and external shocks in business cycle fluctuation in 25 low income countries (LICs) and 17 upper middle income countries (UMICs) for the period of 1960Q1 to 2014Q4. Data for the study were obtained from the International Financial Statistics, the World Bank, International Monetary Fund and the Organization for Economic Co-operation and Development national accounts data file for selected LICs and UMICs. The study formulates a vector autoregression (VAR) model and uses quarterly time series data to investigate the impact of internal and external shocks on business cycle fluctuations.
The objectives of the study are: First, to examine what type of relationship exists between internal and external shocks and business cycle fluctuations. Second, study finds the relative contribution of internal and external shocks to business cycle fluctuations. Third, study examines causality among time series in VAR system. The fourth is to forecast responsiveness of economic fluctuation to internal and external shocks for 10 forthcoming quarters. The study estimates four models to examine the role of internal and external shocks in business cycle fluctuations in case of LICs and UMICs. In the first three models – with three different proxies of financial development – the study measures the contribution of internal shocks in business cycle fluctuation; the fourth model measures the influence of external shocks to explain business cycle fluctuations.
The study introduces financial development, monetary policy and household savings as internal sources and foreign aid, personal remittances, trade openness and climate change as external sources which can affect business cycle fluctuations. The results indicate that financial development (M2, DCB) has a negative and significant association with business cycle fluctuation in the long run in LICs and DCP has positive and significant long run
2
association with economic fluctuation while it has insignificant relationship with business cycle fluctuations in the case of UMICs.
Moreover, household savings positively and significantly affect macroeconomic fluctuation in the long run in LICs while in the case of UMICs; household savings are negatively associated with macroeconomic fluctuation in the long run. Furthermore, in LICs monetary policy stabilizes economic fluctuation by lowering lending interest rate while in case of UMICs contractionary monetary policy stabilizes economic fluctuation. Results also indicate that if any adverse shock to internal and external sources of fluctuations causes the economy to deviate from its equilibrium path, the adjustment process is more rapid in LICs as compared to UMICs. In the case of external sources of fluctuation, the study found that foreign aid and personal remittances negatively and significantly affect economic fluctuation while trade openness and climate change positively affect economic fluctuations in the long run in the case of LICs. However, in the case of UMICs, only trade openness plays a positive and significant role in economic fluctuations while all other external shocks have insignificant association with business cycle fluctuations. The study also found that in LICS the relative contribution of external sources to economic fluctuation is greater than the contribution of internal sources, whereas in UMICs, internal sources contribute more to economic fluctuation than external sources.
The study uses a generalized impulse response function to predict the responsiveness of economic fluctuation against one standard deviation to internal and external sources for future 10 quarters. The results of short-run Granger causality indicate that in LICs, supply of money and domestic credit by banks cause economic fluctuations in the short run while in the case of UMICs, household savings, interest rate and trade openness cause economic fluctuation in the short run.
3
The results of this study may help policymakers to take decisions about financial and real sector development to keep the economy on a certain trend growth path. Moreover, this study will benefit and help future researchers by providing data and information regarding an active set of internal sources- financial development, monetary policy, household savings- that are manageable by a policymaker and a set of external sources- foreign aid, personal remittances, trade openness and climate change - on which policymakers can have little control. Besides, it would also help researchers in the field of banking and economics in further understanding of making use of the VAR framework to find causality dimensions and establish a point of direction for the policymakers with concrete evidence. The study also contributes to the literature by establishing causal relationship between internal and external shocks and business cycle fluctuations.