This paper constructs the Augmented Monetary Conditions Index (AMCI) from 1982:1 to 2004:4 using Unrestricted Error Correction Model (UECM) and bounds test approach for the Philippines data. The results reveal evidence of cointegration between the real Gross Domestic Product (GDP) and its determinants, namely, short-term interest rate, exchange rate, and claims on private sector that take into account three key transmission mechanism channels in the conduct of monetary policy: interest rate, exchange rate, and credit channels. The monetary condition during the study period is reflected in the Bangko Sentral ng Pilipinas’s reaction to the prevailing economic situation, and that the AMCI tracks the inverse movements of the real GDP growth reasonably well, especially after 1990s. The paper also sheds possible light on policy implications.

Monetary Conditions Index (hereafter MCI) is defined as the weighted sum of the percentage point change in the short-term real interest rate relative to their values in a base period, and the percent change in the exchange rate relative to the base period (see Freedman, 1995, p. 75). Empirically speaking, an MCI can be constructed using either nominal or real variables.1 The idea of using MCI as an approximate measure of the state of the overall monetary conditions was pioneered by the Bank of Canada in the late 1980s, followed by New Zealand in December 1996. In the open economies, the inclusion of both interest rate and exchange rate transmission mechanism channels in the conduct of monetary policy are common. Short-term interest rates have been the primary instrument of domestic and foreign monetary conditions for many countries, where changes in the monetary policy stance affect the interest rate and change saving-investment decisions.

In the process of formulating monetary policy, a series of variables could be ranged from the ultimate policy target at one end to the policy instrument at the other end, with operational target, intermediate targets and information indicators in the middle (see Freedman, 1995). First of all, when MCI is featured eminently as an operational target, it shows the degree of easing or tightening of the monetary policy stance relative to a benchmark period. Second, when MCI is used as a policy indicator, it keeps track of both interest rate and exchange rate movements and their effects on Aggregate Demand (AD). Interest rate affects AD through their impact on the intertemporal consumption and saving decisions of households, and the intertemporal investment decisions of firms. Meanwhile, the exchange rate influences AD through the impact on the relative price of domestic- versus foreign-produced goods. Third, when MCI is served as an informative indicator for liquidity conditions in the financial system, it provides information on monetary policy stance by comparing the effects of interest rate and exchange rate on inflation rate (Hansson and Lindberg, 1994). Since exchange rate can be influenced by factors other than monetary policy action, and it is difficult to assess the source of shocks to the exchange rate and appropriate policy responses, the emphasis is now placed on using an MCI as an indicator of monetary and financial conditions, rather than a policy target (Peng and Leung, 2005).

Apart from the interest rate and exchange rate channels, credit transmission mechanism channel influences the conduct of monetary policy stance. On the supply side of the credit market, tight monetary policy reduces banks’ lending ability, as tightening of monetary policy reduces bank reserves, ultimately affecting the quantity of customer deposits (Bernanke and Gertler, 1995; and Bank of International Settlements, 1997). On the demand side of the credit market, tight monetary policy makes borrowers less creditworthy or less eligible for loans (Abel and Bernanke, 2005). The present study is different from the conventional mode of constructing MCI. Here, the augmented MCI (AMCI hereafter) is constructed by incorporating the claims on private sectors to capture credit channel in addition to the interest rate and exchange rate channels. This study employs the Autoregressive Distributed Lag (ARDL) bounds test approach to examine cointegration between the real GDP and its determinants. The weights of the AMCI are derived from the reduced form AD equation. Long-run elasticity will then be calculated in constructing the AMCI index.

Intuitively, an increase in MCI reflects tightening, while a decrease in MCI signifies easing of monetary conditions. Monetary conditions can be tightened by an increase in the domestic short-term interest rate and would induce capital inflows, consequently leading to an appreciation of the exchange rate. Exchange rate appreciation brings contradiction effect to the economy. Hence, tightening of monetary conditions serves to dampen AD, and vice versa. If inflationary pressures have decreased relative to what had been expected, the desired path for monetary conditions is revised downwards. However, if inflationary pressures have increased relative to earlier expectations, the desired monetary conditions should be adjusted upwards (Bank of Canada, 1995). However, previous studies have questioned the weight of MCI. The MCI weight represents the output elasticity with respect to the real interest rate and the real exchange rate on AD. The question now is whether MCI could be a useful indicator of the domestic monetary conditions for the Philippines in facing a more liberalized economy.

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