All the seven featured cooperatives have developed some type of supervision and reporting procedures. In general, the reporting goes from the operational staff to the Management Board and Supervisory Board, with the reporting mainly consists of financial reporting and loan disbursement status. Special meetings will be conducted between operational staff, Management Board, and Supervisory Board to discuss non-performing loans and collection problems. The majority of them have internal audit team (KSP Balo’ta, KOMIDA, BMT Tamzis, Kospin Jasa, and CU Pancur Kasih), and all (except CU Pancur Kasih) has their financial reports audited by external auditors. All the cooperatives send their regular reports to the Local and National Ministry of Cooperatives, and to their secondary cooperatives where applicable.
For the decision making process, the seven cooperatives show different practices despite the fact that all conducted through their RAT mechanism. In general, policy making is done through RAT with a representation system, while operational decisions are made by operational staff in consultation with Management Board, and Supervisory Board.
Representation system is put in place due to the large number of members, coupled with their scattered locations, that makes it nearly impossible to gather all the members in one place for the voting activities. Therefore, they exercise a pre-RAT mechanism to have the representation system in several stages, starting with meeting in groups followed by pre-RAT meetings. The actual RAT are attended by quota-based representatives selected during group and pre-RAT meetings. The representation system is mainly applicable for those with full membership system such as CU Pancur Kasih and KSP Balo’ta. Meanwhile, for those who apply layers in their membership system (semi-full-privilege), it is possible for them to have full attendance as they only have limited number of people with full membership status (who earn the voting rights). Examples include BMT Tamzis, Kospin jasa, and USP Swamitra Koppas Cipulir.
Although RAT is the ultimate reflection of the “togetherness” value, which support the “by the people and for the people” philosophy, the cost factor should be taken into consideration. To organize a full blown RAT is very expensive and cooperatives need to work around it.
For Kospin Jasa, which aim at swift response to competition with their “banking practice”, they can have decisions made through internal meetings between operational staff, Management Board, and Supervisory Board. They resort to this practice to expedite the process and enable them to make decisions without having to go through the RAT mechanism.
One of the big decisions made during RAT is the distribution of profit sharing or SHU. The study found that all the seven cooperatives promote transparency and accountability in their profit sharing policies. They announce the amount openly during the RAT and ask for consensus regarding the allocation and the percentage. In average, they give back 30-50% of the profit to the members, although their definition for members, those who are entitled to receive SHU vary from one to another.
Findings from the survey to the “Saving and Loan Cooperatives’ Management Board”
show the average distribution of Profit Sharing (SHU) is as follows:
40% for members
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20% for business expansion
7% for training and development
It is estimated that the remaining 33% is allocated for the benefits of Management Board and operational staff
Conclusion on this study specifically refers to a previous study conducted in 2013 by the World Bank team10 on “The Different Business Models of Saving and Loan Cooperatives in Indonesia”. The study features case studies on seven saving and loan cooperatives (KSPs) / saving and loan cooperative units (USPs), which consisted of:
1. KSP Ba’lota, Toraja 2. Kospin Jasa, Pekalongan 3. CU Pancur Kasih, Pontianak 4. BMT Tamziz, Wonosobo
5. Koperasi Mitra Dhuafa (KOMIDA), Jakarta 6. USPO Rukun Makmur, Madiun
7. USP Swamitra Cipulir, Jakarta
10 The study on “The Different Business Models of Saving and Loan Cooperatives in Indonesia” was conducted by the World Bank in collaboration with Ministry of Cooperatives (Kemenkop) and the National Planning Agency (Bappenas). The purpose of the study is to gain a better understanding of the different practices and business models exercised by saving and loan cooperatives in Indonesia, particularly on the internal and external influencing factors that lead them to their current practices. Internal factors include governance and membership while external factors include network, competition and market opportunities. The study was conducted through Focus Group Discussions (FGDs), in-depth interviews, and observation, in addition to literature reviews.
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INFLATION TARGETING AS AN ANCHOR OF MONETORY POLICY IN DEVELOPING ECONOMIES – A STUDY WITH SPECIAL REFERENCE TO INDIA
Sagar Patil
Sector 25, Plot No.521, Ashirwad, Pradhikaran, Nigdi, Pune: 411044, Maharashtra, India E-mail: [email protected]
ABSTRACT
Inflation targeting as a monetary policy strategy has been a subject of intense debate of late, especially in India, against the backdrop of the recommendations of the Dr. Urjit Patel Committee set up by the Reserve Bank of India (RBI). This theoretical paper analyzes, in the context of the current macroeconomic conditions prevailing in India and also in light of the experience of other emerging market economies, whether inflation targeting would be a viable monetary policy framework to be pursued by the RBI. Though it is argued that an institutional commitment to predictable and low inflation rates would lead to greater monetary stability, the practicality of fulfilling such a commitment in an economy like India where a significant proportion of inflation is caused by factors such as supply side shocks, which are beyond the control of the Central Bank has always been in question. To hold the Central Bank accountable for something which it can only influence to a limited extent, may in fact, end up damaging its credibility. Also, in the present globalized world where economies are subject more than ever before to external shocks which may require divergent policy responses, this paper tries to analyze whether an inflation targeting regime would come in the way of effective monetary policy response. Finally, this paper also discusses the institutional and economic pre-conditions that are required to be put in place before an economy can adopt inflation-targeting as an anchor for monetary policy.
Keywords: Inflation targeting, monetary policy framework, central banking.
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INFLATION TARGETING AS AN ANCHOR OF MONETORY POLICY IN DEVELOPING ECONOMIES – A STUDY WITH SPECIAL REFERENCE TO INDIA
Inflation Targeting
Inflation targeting is a monetary policy strategy followed by central banks to maintain inflation at a certain level or in a narrow band around a certain level. The strategy of inflation targeting usually involves the following:
1. Public announcement of targeted inflation rate over the medium term by the central bank, leaving some leeway for unavoidable economic shocks;
2. Official recognition of price stability as a primary goal of monetary policy by the central bank, subordinating other goals; and
3. Increased accountability of central banks in achieving the set objectives of monetary policy.
Evolution of Inflation Targeting
Inflation targeting as a monetary policy strategy gradually evolved after the collapse of the Bretton Woods fixed exchange rate system. One of the first proponents of inflation targeting was the Bundesbank – the central bank of Germany, which set the targets of growth in money supply with reference to the banks’ long term desired inflation rate, which was 2%.
There is evidence to suggest that when conflicts arose between growth and inflation, the Bundesbank gave priority to inflation, subordinating growth (Bernanke & Mihov, 1997).
However, the Bundesbank was certainly not explicit in its communication about its inflation targets and hence the thesis that it did actively follow inflation targeting as a monetary policy strategy is not unquestioned.
The central bank of New Zealand was the first to adopt inflation targeting, in its true sense, in 1989. In the 1990s other developed nations joined the league with the central banks of Australia, Sweden, Canada and England also adopting inflation targeting. Soon, this policy framework was adopted by developing economies like Thailand, Brazil, Philippines, Chile, Mexico and South Africa. The US Federal Reserve, though pursuing an unofficial inflation target for a long period of time, made its inflation targeting policy official in January 2012, when it announced that it would pursue a policy which targets a 2% rate of inflation, as it believed that such a policy would be most consistent over the long run with the Federal Reserve’s statutory mandate. The European Central Bank (ECB) has also formally announced an inflation target of up to 2%.
Originally, inflation targeting was interpreted by many policy makers as giving sole priority to maintaining the inflation rate around the targeted level. This made some policy makers skeptical about the long-run viability of the approach of inflation targeting because mere price stability without output near full employment levels would have negative implications in the long-run. As a result, the original and somewhat rigid form of inflation targeting evolved further into what is known as flexible inflation targeting (FIT). In FIT, the focus is on keeping inflation expectations anchored even when actual inflation may deviate from the target at times, in order to achieve near-full employment conditions in the economy.
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In March 2015, in line with the recommendations of the Dr. Urjit Patel Committee, the Reserve Bank of India, India’s central bank, formally adopted inflation targeting as its guide to monetary policy, by announcing that it would target an inflation of 4% in the medium term.
However, the debate surrounding the suitability of inflation targeting in an economy like India still continues.
Arguments in favour of inflation targeting as a nominal anchor
A nominal anchor is central to a transparent and credible monetary policy framework.
It helps in tying down the final goal of monetary policy in the medium to long run and the expectations of economic agents adjust accordingly. Inflation targeting also reduces the likelihood of the central bank falling into a time inconsistency trap. The source of time inconsistency is often found in the form of political pressures on the central bank to follow an over-expansionary monetary policy. Inflation targeting discourages such pressures, as the accountability of the central bank towards meeting its inflation targets is well publicized.
Inflation targeting has gained popularity as a nominal anchor because of the several advantages that it has over other anchors such as exchange rate peg and monetary targeting.
An exchange rate peg exposes the economy to potential external shocks, particularly those emanating from the anchor economy. In contrast, inflation targeting helps monetary policy to focus on domestic considerations.
Monetary targeting refers to a policy whereby the central bank announces that it will achieve a certain value of annual growth rate of a monetary target. It is argued that monetary policy can influence monetary growth rates to a much greater extent than it can influence inflation because of the long time lag involved in the transmission of monetary policy actions. However, the main advantage of inflation targeting over monetary targeting is its visibility. A much larger portion of the population understands the meaning of inflation as opposed to monetary growth. This plays a crucial role in managing inflation expectations.
Another major advantage of inflation targeting is the transparency of policy associated with it. If the central bank has sufficient credibility that the economic agents believe that the inflation target will be hit, they would in turn negotiate their returns (such as wages, rent, etc.) on the basis of low and stable inflation expectations. Thus, the policy would be self-reinforcing: low inflation expectations would lead to low inflation, confirming the low expectations and so on.
It is also argued that price stability is a pre-condition for sustainable growth in the medium run, though a trade-off between inflation and growth is inevitable in the short run.
Empirical evidence suggests that countries that have adopted inflation targeting have tended to have lower and more stable inflation after the change than before.
Another variant of inflation targeting that is being actively considered by some central banks is price level targeting. In price-level targeting, the central bank would adjust it monetary tools, which typically are short term interest rates, in an effort to achieve a pre- announced level of prices over the medium term. This approach differs from inflation targeting, as inflation targeting endeavors to achieve a pre-announced level of increase in prices. Price-level targeting could have some potential benefits over inflation-targeting.
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Particularly in the economic environment in developed economies, where policy rates have fallen to near zero, price-level targeting could help support positive inflation expectations, thereby stimulating growth. However, a major hurdle in the approach of price-level targeting is the complexity involved in communicating the price targets to the masses.
Evolution of monetary policy framework in India
In the early years after gaining independence in 1947, monetary policy in India was characterized by an exchange rate anchor. In 1957, this policy was replaced by the use of credit aggregates as the nominal anchor. Cash Reserve Ratio (CRR) and Bank Rate were the main policy tools in the hands of the Reserve Bank of India (RBI), which focused on selective credit control and enhancing flow of credit to socially important sectors.
The period of 1971-85 was characterized by heavy fiscal deficits as a result of the public sector oriented growth model adopted by the government. The resultant monetization of the fiscal deficit exerted considerable inflationary pressures on the economy and the central bank had to often use the CRR to neutralize inflation. Credit to the private sector remained subdued during this period.
After 1985, in line with the recommendations of the Committee to Review the Working of the Monetary System, monetary targeting was adopted as a nominal anchor to monetary policy. However, evidence suggests that the monetary targets set by the central bank were rarely met. The biggest hurdle in achieving this end was demand for credit from the government in wake of high fiscal deficits and the lack of control of the RBI over such demand. Further, with the opening up of the Indian economy in the 1990s and the resultant capital flows, controlling monetary aggregates became difficult than ever before. With the economy being exposed to global dynamics, volatility in exchange rates and transmission of external shocks imparted considerable instability to demand for money.
Eventually in 1998, the RBI adopted a multiple indicator approach to monetary policy. As per this approach, the RBI would consider a number of factors such as inflation, exchange rates, fiscal position, demand, output and credit growth in formulating monetary policy. The focus also shifted from controlling monetary aggregates to influencing economic activity predominantly with the tools of interest rates. The multiple indicator approach worked fairly well till 2008-09, with an average real GDP growth rate of around 7.1% and average Wholesale Price Index (WPI) as well as Consumer Price Index (CPI) based inflation of around 5.5%. However, since 2008-09, though GDP growth rate has been moderating, inflation has tended to remain at fairly elevated levels. These signs of stagflation reopened the debate about whether the multiple indicator approach was the right one to pursue. Critics of this approach argued that using a large spectrum of indicators did not provide a clearly defined nominal anchor for monitory policy. It also created uncertainty about the precise indicators that the RBI took into consideration while framing monitory policy.
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Table 1: Mean Inflation Rates in India and Contribution to Overall Inflation Year WPI Contribution to inflation in percentage points
Food Items Non-food Articles
Fuel Group and Minerals
Non-food Manufacturing
1990-91 10.3 2.8 0.7 1.1 5.3
1991-92 13.7 4.5 0.8 1.2 6.9
1992-93 10.0 2.9 0.0 1.2 7.1
1993-94 8.3 1.8 0.4 1.6 4.6
1994-95 12.6 3.7 1.0 1.0 7.5
1995-96 8.0 1.1 0.4 0.5 6.1
1996-97 4.6 2.0 0.0 1.1 0.8
1997-98 4.4 1.5 0.1 1.4 1.1
1998-99 5.9 2.8 0.5 0.4 1.7
1999-00 3.3 1.6 -0.3 1.0 1.8
2000-01 7.2 -0.8 0.1 3.4 2.9
2001-02 3.6 -0.1 0.2 1.3 1.3
2002-03 3.4 0.9 0.3 0.8 1.1
2003-04 5.5 1.6 0.5 1.0 2.7
2004-05 6.5 0.9 0.0 1.8 3.6
2005-06 4.4 0.9 -0.1 2.2 1.5
2006-07 6.6 1.9 0.2 1.4 3.1
2007-08 4.7 1.4 0.5 0.2 2.7
2008-09 8.1 2.2 0.5 2.2 3.1
2009-10 3.8 3.6 0.2 -0.1 0.1
2010-11 9.6 3.0 1.0 2.4 3.1
2011-12 8.9 2.0 0.5 2.9 3.6
2012-13 7.4 2.5 0.5 1.9 2.4
2013-14 6.0 2.1 0.3 1.6 2.0
2014-15 2.1 0.9 0.0 -0.1 1.3
Source: Patel (2014)
Finally in March 2015, in accordance with the recommendations of the Expert Committee to Revise and Strengthen the Monitory Policy Framework, headed by Dr. Urjit Patel, Deputy Governor of RBI, the RBI formally announced a shift in its policy towards adopting inflation targeting as a nominal anchor of monetary policy.
Challenges in implementation of inflation targeting in India
For a long time, questions have been raised about the practicality of inflation targeting as a nominal anchor of monetary policy in an economy like India. The primary hurdle has been the way in which inflation is measured in India. Until recently, the central bank communicated inflation projections based on the Wholesale Price Index (WPI) alone, essentially because it was the only measure of prices at the national level. The WPI is an imperfect substitute to the Producer Price Index (PPI). Importantly, it does not capture price movements in non-commodity producing sectors such as services, which account for close to two-thirds of the economic activity in India. Additionally, all prices taken for the calculation