Why Did Israel Change Its Monetary Policy at the End of 1984? The Role of Monthly Data

The high annual inflation rates in Israel between 1978 and 1984 of 42.5 percent to a record rate of 444.87 percent in 1984 pressed the authorities to fight the inflation. This research set out to find the cause of inflation, focusing only on the period leading to policy changes. Using the vector autoregressive (VAR) methodology, the research tested causality relationships between inflation and effective exchange rate, i.e., exchange rates that include import taxes, custom duties, surcharges, purchase tax, and funds on imports. This research is novel for using monthly data for all the relevant variables for the first time. The paper’s objective is to illustrate that the application of higher-frequency monthly data and standard analytical tools available at that time was sufficient to drive a substantive policy change. This simple methodological change marked a significant move away from the established practices that relied on quarterly data for modeling import taxes within the Israeli economy. The findings reveal that straightforward VAR modeling with monthly data and first-differences, the standard tools at the time, was enough to change the inflation-control policy. Consequently, the previous accommodating monetary policy was replaced by a nonaccommodating monetary policy. The accommodating money supply policy allowed inflation to persist during the time of the study. The shift of the Israeli monetary policy to be less or nonaccommodating helped contain inflation and subsequently advance the Israeli economy. The research’s main insight is that opposite policies to those in place before 1984 should have been adopted to fight inflation. Gaining access to monthly data on all relevant variables for the first time in Israel was a simple but crucial change that made this policy shift possible. This development was essential, leading to important reforms in both monetary and fiscal policies, as well as changes in how frequently data are reported. Finally, this case study also reinforces the principle that the acquisition of timely, high-frequency, high-quality data is essential for credible research.