The main points in this section are the following: First, real-world in‡ation targeting can be interpreted as a targetingrule, with a relatively explicit loss function to be minimized. Un- controversially (by now), this loss function also contains concerns about the stability of the real economy, for instance, output variability. That is, it corresponds to “‡exible” rather than “strict” in‡ation targeting. Second, the targetingrule can also be expressed as an intermediate- targetingrule, which I shall call “in‡ation-forecast targeting” (although arguably a more precise but somewhat clumsy name would be “in‡ation-forecast-and-output–gap-forecast targeting”). Then the conditional in‡ation forecast is an intermediate target variable (or both the conditional in‡ation and output-gap forecast are intermediate target variables). Third, in‡ation targeting appears to be a commitment to a systematic and rational (that is, optimizing for the given loss function) monetarypolicy to a greater extent than any other monetarypolicy regime so far. This is because the operating procedure under in‡ation targeting, in‡ation-forecast targeting, can be interpreted as a way of ensuring that …rst-order conditions for a minimum of the loss function are (approximately) ful…lled. Also, the high degree of transparency and accountability associated with in‡ation targeting allows outsiders to monitor that those …rst-order conditions are ful…lled and creates strong incentives for the central bank not to deviate.
This article reviews the Thailand monetarypolicyrule and its performance under the adoption of inflationtargeting regime since 2000. The study estimates the policy reaction function to see if the inflationtargeting has been linked with an inflation-responsive monetarypolicyrule, and investigates whether the monetarypolicyrule would actually have its transmission effect on inflation, through tracing the impulse responses of inflation rate to monetarypolicy shocks in vector autoregressive (VAR) and structural VAR models. The study contributes to the literature by updating the assessment of the Thailand monetarypolicy through covering the period after 2015, when the Bank of Thailand has upgraded its inflationtargeting framework by transforming it from range target to point target to provide a clearer policy signal to the public. The main findings are as follows. The estimation outcomes of the policy reaction function show that the Thailand monetarypolicyrule under the inflationtargeting is characterized as an inflation- and exchange- rate- responsive rule with forward-looking manner, which is countercyclical against inflation in the long run, but is accompanied with slow adjustment toward a target policy rate. The results from the impulse response analyses imply that the Thailand monetarypolicy under the inflationtargeting has only a marginal transmission effect on inflation probably due to the slow adjustment of policy rate.
We interpret the estimation results above as follows. First, the current BOM appears to have adopted the inflation-responsive and forward-looking (one quarter ahead) monetarypolicyrule under its inflationtargeting framework. It might reflect the progress in inflationtargeting framework toward forward-looking mode by adopting the FPAS since 2011. Second, the current BOM inflation-responsiveness is, however, not powerful enough to stabilize inflation in the sense that the real policy rate tends to be still pro- cyclical to inflation pressure. The Mongolian β magnitude, just 0.444, is in contract to those of advanced nations with more than unity that Clarida et al. (1998b) estimated. It should also be noted, however, that the policy rate is not the only instrument but often supplemented by the reserve requirement ratio in Mongolian monetarypolicy. Third, the Mongolian monetarypolicyrule is also responsive to exchange rate movement. The policy reaction to exchange rate is typically represented by the fact that the BOM has still kept its policy rate at more than ten percent even under the inflation rate below the targeted rate after 2015 to prevent currency value from falling. This kind of exchange- rate reaction, so-called “fear of floating”, tends to sacrifice monetary autonomy: the “fear of floating” might weaken the policy reaction to inflation and output gap. As a matter of fact, the estimation result in this study shows the less-than-unity β magnitude and the negative reaction of production gap.
The purpose of this article is to examine whether inflationtargeting affects the volatility of inflation and enhance economic growth. We also verify the effectiveness of this policy through the achievement of economic performance. Thus, we hope to achieve two goals in this work: one is to contribute to the economic literature on the topic; and the other is to have a more reliable yardstick available before recommending that any Central Bank joins the inflationtargeting framework. Our empirical technique recently used by economists in the case of the theory of inflationtargeting in developed countries. Indeed, we have adopted the Great Moderation approach of Pétursson (2005) that address one methodology well known in the literature. Than by using panel data, we test the effect of inflationtargeting while controlling for the “Great Moderation”. The most important advantage, “Great Moderation” approach gives us information about the stability of inflation and growth in developing countries that have adopted (IT) by the end of 2007 (called ITers or treatment group) and non ITers (or control group).
What is generally the role of instrument rules in monetarypolicy? In practice, no central bank follows an instrument rule, either explicit or implicit. Every central bank uses more information than the frequently suggested simple rules rely on, especially in open economies. In particular, no central bank reacts in a prescribed mechanical way to a prescribed information set. As is known by every student of modern central banking, the bank’s Board or MonetaryPolicy Committee reconsiders its monetarypolicy decisions more or less from scratch at frequent intervals, by taking all the relevant information into account (with the possible exception of a …xed exchange rate). The bank frequently reconsiders (and, at best, reoptimizes); rather than considers (and, at best, optimizes) once and for all, and then simply applies the resulting reaction function forever after. This reconsideration of the bank’s decisions means that the situation is best described as decision-making under discretion rather than commitment; there will inevitably be reconsiderations and new decisions in the future, and there is in practice no commitment mechanism to prevent this. 15
Markov-switching model that makes its use for the analysis of time variance in the monetarypolicyrule rather questionable. The model assumes sudden switches from one policy regime to another rather than a gradual evolution of monetarypolicy. Although at first sight one may consider the introduction of IT to be an abrupt change, there are some reasons to believe that a smooth monetarypolicy transition is a more appropriate description for IT countries (Koop et al., 2009). Firstly, the IT regime is typically based on predictability and transparency, which does not seem to be consistent with sudden switches. Secondly, it is likely that inflation played a role in interest rate setting even before the IT regime was introduced, because in many countries a major decrease of inflation rates occurred before IT was implemented. Thirdly, the coefficients of different variables (such as inflation, the output gap or the exchange rate) in the monetarypolicyrule may evolve independently rather than moving from one regime to another at the same time (see also Darvas, 2009). For instance, a central bank may assign more weight to the observed or expected inflation rate when it implements IT, but that does not mean that it immediately disregards information on real economic activity or foreign interest rates. Finally, there is relevant evidence, though mostly for the U.S., that monetarypolicy evolves rather smoothly over time (Boivin, 2006; Canova and Gambetti, 2008; Koop et al., 2009). Therefore, based on this research, a smooth transition seems to be a more appropriate description of reality. In a similar manner, it is possible to estimate the policyrule using STAR-type models. Nevertheless, it should be noted
the Markov-switching model that makes its use for the analysis of time variance in monetarypolicyrule rather questionable. The model assumes sudden switches from one policy regime to another rather than a gradual evolution of the monetarypolicy. Although at first sight, one may consider the introduction of the IT being an abrupt change, there are some reasons to believe that the smoothed transition of monetarypolicy is more appropriate description for the IT countries (Koop et al., 2009). Firstly, the IT regime is typically based on predictability and transparency, which does not seem to be consistent with the sudden switches. Secondly, it is likely that inflation played already a certain role for the interest rate setting even before the IT regime was introduced, because in many countries the major decrease of inflation rates occurred before the IT was implemented. Thirdly, the coefficient of different variables (such as inflation, the output gap or exchange rate) in the monetarypolicyrule may evolve independently rather than moving from one regime to another at the same time (see also Darvas, 2009). For instance, a central bank may assign more weight to observed or expected inflation rate when it implements the IT but it does not mean that it immediately disregard the information on real economic activity or foreign interest rate setting. Finally, there is relevant evidence, though mostly for the U.S., that the monetarypolicy evolves rather smoothly over time (Boivin, 2006, Canova and Gambetti, 2008, Koop et al., 2009). Therefore based on this research, a smooth transition seems to be a more adequate description of the reality. In a similar manner, there is a possibility to estimate the policyrule by STAR-type models. Nevertheless, it should be noted that STAR-type models assume specific type of smooth transition between the regimes, which can be more restrictive than flexible random walk specification that we employ in this paper. Therefore, we leave the empirical examination of Markov-switching as well as STAR-type models for further research. 5
Armed with this set of transition matrices, we next find a solution of the original problem using standard dynamic programming. Clearly, because we consider a subset of the possible states of the economy, this discretization is only an approximation. Moreover, it should be clear that in the neighborhood of the borders of the rectangle (a F , b F ) ´ (a y , b y ) the approximation is far from accurate, for two reasons. One is that the probability of moving further away from the center of the rectangle is assumed to be zero, and the other is that the centers of the small rectangles q j at the borders do not properly represent the values that the system can take outside the (large) rectangle. When we calcu- late optimal policy rules, we use the complete rectangle, but we only consider the neighborhood of its center when we analyze and compare the implications of alternative loss functions.
Initially, we turn our attention to the stock market. Results are shown in table 3. The positive sign assumed by the coefficient pertaining to the monetarypolicy instrument in both the 1 st and the 3 rd regression equation, implies that rises in the short-term interest rate increase the probability that the stock market will remain at the high risk regime. This result accords with Chen (2007). However, the relationship appears to be statistically significant only when we consider all variables together (i.e., in the 3 rd regression equation where all control variables have been included). What is more, the lagged value of the probability itself also has a key role to play. In addition, as evidenced in the 2 nd and the 3 rd regression equation, upward adjustments in both markets induce the stock market away from the high-volatility regime (i.e., the relevant coefficients assume a negative sign). Finally, the coefficient of CPI inflation assumes a positive sign implying that rises in the inflation rate induce the stock market to remain in the high-volatility regime. We can therefore reach two important conclusions regarding the stock market in the UK. First, abrupt increases of the policy instrument do not help remove volatility from the market. Second – given the inflationtargeting character of the monetarypolicy in the UK – successfully anchoring expectations regarding future inflation rates is very important because higher levels of inflation induce the stock market to remain at the high-volatility regime. On a secondary level, given the negative coefficient relating to HALIFAX, we are able to provide some initial evidence regarding the interrelation between the housing and the stock market. To be more explicit, results indicate that higher housing prices help the stock market move away from the high-volatility regime.
1998 to control liquidity and ease the pressure on the foreign exchange market. As a result, the fortnightly average CMR reached an historical high of 50% in the fortnight which ended January 30, 1998. This historical fact is supported by the estimated shocks from our model where we see a spike exactly in the same month. In the period from 1999 to 2000, the Indian economy faced challenges on several fronts. On the one side, there was acceleration in global output and trade due to the continuing strength of the U.S economy and sharp recovery of the Asian economy, but on the other side the gains from global economic recovery were eroded by a more than doubling in oil prices due to production curbs by OPEC. For oil importing country like India, this oil price surge translated into inflationary pressure and constriction of import purchasing power. During this period monetarypolicy remained mainly tight due to inflation considerations and also the sporadic volatility of the foreign exchange market. This is also indicated by the graph of CMR shocks. The „repo rate‟ reduction in October 30, 2002 brought down the call money rate as also evident from the figure. The period of 2002-03 was characterized by ample liquidity in the economy due to sustained accretions of capital inflows, contraction in food credit and liquidity overhang. Monetarypolicy was mainly loose and this is also indicated in the figure. The period of 2003-2004 was a period of uncertainty for financial markets due rising oil prices and their impact on inflation and growth. There was an increase in interest rates from record lows as seen in 2003-04 due to the international trends and rise in inflation. This slight reversal in trend has also been observed in our estimated shocks.
One such area in which our understanding can be improved con- cerns the credit markets. A fundamental problem is that we presently lack the analytical tools that accurately capture the role played by credit and house prices in the economy. The research of Chairman Bernanke and others regarding the importance of collateral constraints and the financial accelerator effects on firms investment have paved the way for an increased understanding of these complex issues. 3 Their research has been extended by others to the household sector—the idea being that as house prices increase, credit-constrained households are able to engage in so-called mortgage equity withdrawals and raise their con- sumption. In time, insights from these models will help us to better analyze house prices and household debt in integrated, general equilib- rium setups. In fact, this is an area into which the Riksbank is putting some modelling efforts, trying to understand how credit markets can be integrated with our general equilibrium approach to fluctuations in growth and inflation. 4
If this is the objective of increased transparency, then simply summing some arbitrarily chosen characteristics is of little help since it tells us nothing about which characteristics are more important than others (a ranking which may, moreover, vary across regimes). It seems entirely plausible that one or maybe two key institutional features are sufficient after which the rest are redundant, even though they create an impressive score in the league tables. We should always bear in mind Daniel Thornton’s (2003) caution that two of the most secretive central banks, the Swiss and the German pre-1999 Bundesbank, were amongst the easiest to read as well as the most successful in their conduct of policy. Provided a central bank behaves consistently, in response to events (and often enough), agents with large sums at stake will eventually learn to predict simply on the basis of constant conjunction.
Another important consideration from monetarypolicy prospective is to keep balance in external accounts. As external imbalances are considered potential threats to economic as well as financial stability in the country (Bonga, 2019). Mundell (1962) emphasized the role of monetarypolicy in correcting the external imbalances. Duarte and Schnabl (2015) finds that monetarypolicy rather the exchange rate is main determinant of current account balance in East Asia and oil-exporting countries. F igure 3 provides a comparison of current account position of inflationtargeting versus other countries. Though current accounts are in deficit for both types on average, these are much more severe in case of non-inflationtargeting countries. Both types have shown improvements in current account deficits, however, it is more pronounced in case of the non-inflationtargeting countries in recent periods. So again the IT framework does not offer any advantage over other alternatives practiced by non-inflationtargeting countries on improving the external position. It even performs poorly on these fronts despite the fact that inflationtargeting group is less open as compared to other group.
In our paper we consider a two-country model. In each country there are two sectors: the intermediate goods sector and the final goods sector. Intermediate goods are used in the production of final goods in both countries. Final goods enter the consumption basket of domestic and foreign consumers. Furthermore, we assume that workers are monopolistic suppliers of differentiated labour services and they set their wages according to Calvo contracts (1983). Producers in both sectors are also monopolistic suppliers of differentiated goods. More precisely we assume that market power allows them to price discriminate between domestic and foreign markets. Therefore, breaking down the law of one price (LOP) we allow for different price dynamics of the same good in different countries. Finally, since firms in both sectors set prices in buyers’ currency 2 we introduce imperfect exchange rate pass-through. In fact, when a shock occurs and the exchange rate changes only a fraction of firms adjust prices to react to the exchange rate fluctuations. In this way we introduce many different sources of nominal inertia. In each country we have sluggish adjustment in nominal wages, in prices of domestic and imported intermediate goods and in prices of domestic and imported final goods. This makes our model a particularly suitable framework within which to address the question of what measure of inflation the central bank should target. In this paper we have chosen to restrict ourselves to consider two alternatives: output price inflation and consumer price index (CPI). The first choice is due the fact that, as already mentioned, a policyrule formulated in terms of a measure of output prices has been recognised as the optimal one even in open economy. However, most of these results have been derived in
11. A good example is the Bank of Canada, which until recently stated the rationale for its policy as follows: “Inflation control is not an end to itself; it is the means by which monetarypolicy contributes to solid economic performance. Low inflation allows the economy to function more effectively. This contributes to better economic growth over time and works to moderate cyclical fluctuations in output and employment.”
22 regime, authors such as Sims (2003), Lomax (2004), as well as, King (2012) argue that monetarypolicy decision making could sometimes entail unconventional results for the stock market as within an inflationtargeting regime it is the actual and the expected levels of inflation that matter the most for economic developments; implying that issues relating to interest rate and money growth changes are relegated to a secondary level. In this regard, any rises in the level of interest rates could even be perceived as a positive signal from market participants in the sense that the monetarypolicy authority is consistently responding to its main task which is to successfully control inflation in the economy. According to Bomfim (2003), removing the element of surprise from the monetarypolicy decision making process, greatly affects the results we obtain regarding the impact of monetarypolicy in the volatility observed in the stock market. In testament to this, Li et al. (2010) in analysing the effects of monetarypolicy on the stock markets of Canada (one of the first countries to adopt an explicit inflation target in 1991) and the United States (a country which has not set an explicit inflation target) document that rises in the monetarypolicy instrument interest rate are far more greater in magnitude and more time-persistent in the US than they are in Canada. On the whole, these suggestions appear to be in line with authors such as Bean (2003), Lomax (2004), as well as, King (2012) who broadly argue that the adoption of an explicit inflation target by the Government and the pursuit of this target by an independent monetarypolicy authority can actually bolster confidence and lead to better macroeconomic results.
This paper addresses recent developments in monetarypolicy the- ory in the context of a binding Zero Lower Bound and discusses the possible evolution of monetarypolicy after the Great Recession. We start from Olivier Blanchard’s suggestion that a higher inflation tar- get and correspondingly higher interest rates would offer larger wiggle room for Central Banks to stimulate the economy through monetary easing without hitting the ZLB and might thus prove to be a desir- able policy. Using a New-Keynesian DSGE framework and including positive steady state inflation, we investigate if having a higher per- manent inflation target would improve welfare and find that this is unlikely. Furthermore, we address the possibility of having temporary higher inflation targets and the effect this could have on economic fundamentals. Finally, we discuss whether simple inflationtargeting suffices or if monetarypolicy might evolve in the aftermath of the cri- sis towards including several objectives and/or instruments, so as to better respond to future economic downturns.
The Organization for Economic Co-operation and Development (OECD) released a report which was titled “MonetaryPolicy in a Changing Financial Environment”. In it they comment on the new, and important, considerations for policy makers. This includes the fact that between 1985 and 1998 the value of the total outstanding debt and equity has increased from 150% to 250% of the GDP’s of the largest OECD economies. They go on to say that monetarypolicy does play an important role in financial stability because through policy decisions borrowing costs for firms and households as well as the value of asset prices change which influences behavior through their impact on the balance sheets. The report also states the greater integration of global capital markets will amplify the sensitivity of asset prices to interest rate movements and monetarypolicy The difficulty for central bankers is how to deflate a price bubble when it begins to form by increasing interest rates but without causing the entire economy to collapse.
In recent years, InflationTargeting (IT henceforth) has emerged as a dominant monetarypolicy strategy for many developed and developing countries. Account by Epstein and Yeldan (2008) showed that the IT monetarypolicy framework was adopted by twenty-four countries as at 2006. Between 2006 and 2009 four additional countries joined the league of inflation targeters bringing the total number to twenty-eight (Jahan, 2012). The only countries that have abandoned IT after they started it, according to Jahan (2012), are Finland, Spain, and the Slovak Republic, following the adoption of the euro as their domestic currency. Nigeria was said to have indicated her interest to adopt the IT framework by the year 2007 (CBN, 2007). However, to date (2014) no such official declaration has been made public yet. Instead, indication is that the Central Bank Nigeria (CBN) may have soft-pedaled in the pursuit of full-fledged IT for the country (Sanusi, 2010). The growing popularity of the IT framework stems from the realization that inflation constitutes a major obstacle to economic growth and efficient resource allocation in the economy. It is argued that inflation distorts prices, diverts capital to rent- seeking activities, compounds social and political problems, frustrates economic planning, encourages capital flight, discourages savings, reduces investment, retards economic growth and development, serves as tax on the poor and ultimately, reduces the living conditions of the people (Debelle, 1999).
As the transition evolved, hard pegs became increasingly burdensome as the combination of fixed exchange rates and the residues of high inflation led to real currency appreciation and, subsequently, to current account deficits and the deteriorating risk structure of capital inflows. These unfavourable developments prompted the monetary authorities to devise various exit strategies from hard pegs toward autonomous monetary policies with flexible exchange rates (Corker, et. al., 2000). After rather unsuccessful experiments with interest rate targeting, monetary base targeting (in Poland), and targeting exchange rate bands with crawling devaluations, central banks of several transition countries with now fairly well-developed financial markets adopted DIT strategies (Masson, 1999; Orlowski, 2001; Jonas and Mishkin, 2003). The Czech National Bank (CNB) did so in January 1998, the National Bank of Poland (NBP) in January 1999, while the National Bank of Hungary (NBH) deferred a similar move until May 2001. The actual implementation of DIT stirred a heated debate over its timing, the exact format and the overall rationale. At least in the case of Poland, the new policy action was characterised as a bit premature by Christofferssen and Wescott (1999) since the country’s average monthly annualised CPI headline inflation in 1998 was still running at 11.9 percent and the functional relationship between inflation and other monetarypolicy variables was imprecise and highly unstable. Without doubt, the three examined countries did not satisfy the prerequisites for DIT inception stated by Mishkin (2000), particularly the requirements of single- digit inflation, a stable relationship between inflation and policy instruments, and the well- defined channels of monetarypolicy transmission. Yet, their strong commitment to disinflation and confidence about the future monetary stability prevailed over the existing institutional deficiencies (Jonas and Mishkin, 2003).