Introduction
Inflation targeting (IT) is a seemingly attractive option for developing countries—or less developed countries (LDCs); but upon closer inspection, IT turns out to be an unwise imitation. The word inflation has been demonized since Alexander del Mar mainstreamed it. However, in reality inflation at moderate levels is good for an economy. Studies have shown that a low level of inflation has positive implications for the economy, while high inflation has the opposite effect. Therefore, keeping inflation in an ideal range becomes a natural goal for central banks (CBs).
The rationale behind the push factor towards inflation targeting is not a puzzle. A non-exhaustive list of high-inflation costs includes: decrease in efficiency, depreciation of savings and outflow of capital. It was no surprise, then, that the world welcomed inflation targeting, which started with New Zealand’s CB in 1989. Since then, the policy has gone global. CBs that follow inflation targeting include those of the biggest economies in the world, such as the United States and Australia. Recently, developing countries such as India have also added themselves to this group. Such a global following is built on sound theoretical and practical justifications.
Theoretically, inflation has been supported by economists since the early 1980s, when they started designating inflation as a monetary phenomenon. According to Milton Friedman, “Inflation is always and everywhere a monetary phenomenon”. The CB aims to control inflation by controlling its root cause, which is the money supply (MS). This control of the MS requires a monetary-policy framework (MPF). In IT, an announced inflation target is achieved via a MPF. This target can be a range of inflation values or a fixed percentage figure. Such theoretical rule-based reasoning has been validated by practical experience.
IT’s encouraging track record starts from the very first example in New Zealand. New Zealand saw falling inflation without incurring significant costs. Other similar experiences prompted Frederic Mishkin to quip that “inflation targeting appears to have been successful in increasing the transparency of monetary policymaking and in lowering significantly the rate of inflation in these countries, without any negative consequences for output”. This general statement was supported by many specific studies. One of these enquiries concluded that an inflation-focused monetary policy has increased the resilience of developed countries in facing supply shocks. Such shiny credentials have misguided many into proposing IT for LDCs.
IT, for all its benefits, would be an ineffective tool for developing countries because of their unique constraints. These constraints are political and economic in nature. The first and foremost issue is the fact that IT belongs to rule-based decision-making. Rule-based thinking has its roots in long-term decision-making. This is always a hard sell in developing countries, owing to their short-sighted monetary and fiscal habits. Furthermore, developing countries keep exchange rates as nominal anchors in their MPFs for a number of reasons.
Apart from having to juggle competing monetary anchors, CBs in LDCs have to operate in a co-dependent existence with the local political bodies (LPBs). Therefore, LPBs play a part in violating the independence of CBs. This acrimony between CBs and LPBs rears its ugly head in the fiscal and modeling aspects of IT. All of these above-mentioned impediments are discussed in detail in the following paragraphs.
Obstacles on the path to a managed inflation rate
Exchange-rate management is more important.
Inflation control comes at the cost of the ability to control the exchange rate, which is non-negotiable for many LDCs. Free exchange rates might be a good policy for developed countries. However, LDCs have to anchor their exchange rates for a number of reasons. The most important argument is the large import content in production as well as consumption. Moreover, debt funding for investment projects is priced in foreign currencies. Therefore, an exchange-rate variation can have adverse effects on the rates of return of these projects. In addition, LDCs that are “cursed” with natural resources have to manage such situations as Dutch disease. All these reasons force LDCs to prioritize exchange-rate control over IT. This argument only gains strength after considering the relatively brittle supply chains of developing countries.
Random supply shocks affect prices.
LDCs have to implement IT in countries with fragile supply chains. Developed-country supply chains are relatively resilient. This is because LDC supply chains suffer from dependency and capacity issues. Therefore, exogenous-supply shocks can cause large short-term price variations. This is an issue because IT is designed to control long-term inflation. Therefore, a short-term shock such as crop failure would fly under the protective shield of IT. A similar incident happened in Pakistan when a flood in 2010 led to food inflation in Pakistan. A constant stream of such shock-induced short-term inflation spells will undermine the utility of IT, which will take the wind out of the argument for IT.
Fiscal deficit forces MS increase.
Even without short-term inflation, IT would have to face the headwinds of low CB independence. Developing countries often suffer from fiscal deficits (FDs) that force political bodies to intervene in CB policy. This intervention comes in the form of inflationary MS increases and cyclical fiscal spending. The issue of fiscal deficit is often difficult to solve for LPBs because it is part of the twin deficits of current account deficit (CAD) and FD. Such situations create strong incentives for the political bodies, democratic or authoritarian, to intervene in CB policy. This results in CBs compromising IT in favor of short-term crisis management.
Furthermore, IT is a joint effort between LPBs and CBs. This means that the government has to perform rule-based spending. Such lofty aims don’t stand up to the political-economic realities of LDCs, which increase spending pre-elections. Similarly, the pendulum swings back in the post-election years; post-election fiscal policy focuses on dealing with the fiscal indiscipline before the election. This destructive cycle is known as political-cycle spending. Such cyclical spending is inconsistent with IT, which requires a more stabilized approach. Similar institutional barriers further complicate implementation of IT.
Weak institutions and IT
Developing countries often suffer from weak institutions. National statistical agencies are also among these institutions. An IT policy is as good as the model and the data upon which it is based. Such models and data are taken for granted in the developed world. However, collecting data in an undocumented economy can be a battle within itself. According to the International Labour Organization (ILO), more than 60 percent of the global workforce is employed in the informal sector.
Informal economies force economists to rely on collected sample data. This data is often distorted because the biggest collection agencies are government-owned. Even private data-collection bodies require approvals from LPBs. This makes economic modeling biased due to non-representative samples. Therefore, even if there is an independent CB with no exchange-rate anchoring or supply-channel constraints, there is a strong chance of it using an inappropriate MPF.
Conclusion
IT for LDCs joins a long list of policies that are being propagated just because they worked in developed countries. Such suggestions reek of neo-colonial ignorance about local political and economic landscapes. It is difficult to implement IT in LDCs because of the many economic and political barriers. The economic impediments include exchange-rate commitments for developing countries. There are numerous reasons for maintaining a managed float exchange rate. In addition to exchange-rate requirements, LDCs often suffer from twin deficits, which include CAD and FD. These deficits force CBs to launch MS increases that have inflationary consequences. Furthermore, CBs in developing countries have to create their economic models on the basis of faulty and incomplete data. In the informal economies of the LDCs, CBs have to work on approximations that lead to misguided MPFs.
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