چکیده:
Reliable measures of the size and direction of changes in monetary policy are very crucial for examining the effects of monetary policy on the economy. Monetary Condition Index (MCI) can be used as a tool to assess the stance of monetary policy. This index is defined as the weighted average of different monetary transmission mechanism relative to their values in a base period. The weights in MCI are the relative importance of each channel in transmitting monetary shocks in the economy. In this paper we construct a new MCI for Iran that characterizes three key innovations. First, for estimation of MCI’s weights, we employ system of equations (VARX) in order to solve the problem of exogeneity arising from single equation method. Second, beside exchange rate and credit channel, it includes asset price channel. Third, we utilize a quarterly data set which seems more plausible for studying short-run dynamics regarding the monetary policy. Our estimated index over the 1991Q2-2014Q1 indicates that in more than 74% of quarters under consideration, monetary condition in Iran is easing relative to the base period (2004:2). The empirical results show MCI leads roughly 1 quarter ahead of inflation. Therefore, this index can be used as the leading indicator of the inflation rate.
خلاصه ماشینی:
This index is defined as the weighted average of different monetary transmission mechanism relative to their values in a base period.
Our estimated index over the 1991Q2-2014Q1 indicates that in more than 74% of quarters under consideration, monetary condition in Iran is easing relative to the base period (2004:2).
In other words, we constructed the MCI for Iran as a weighted sum of three monetary transmission channels consisting of exchange rate, credit, and asset price.
Second, for estimation of MCI’s weights, we applied a vector autoregressive model with exogenous variable (VARX) to identify and measure the importance of different monetary transmission channels in Iran.
We found that the estimated MCI indicates that in more than 74% of quarters under consideration, monetary condition in Iran is easing relative to the base period (2004:2).
First, a benchmark VAR model (introduced in previous section) is estimated, and the impulse response of a target variable (output growth or inflation) with respect to a monetary policy shock is calculated.
Table 5: Relative Weights of Channels (View the image of this page) Source: authors’ calculations For output growth as a target variable, the exchange rate has the highest weight in short and medium terms.
5. MCI Calculation As shown historically in section 2 and empirically in the previous section, the monetary policy would affect Iran’s economy through three different channels: exchange rate depreciation, credit growth, and asset price inflation.