Measuring financial capability of the street vendors

Amidst all the chaos, team RBI continues to function. Just pointed to an interesting short paper on state-wise impact of demonetisation on deposits and cash usage.

Came across this interesting paper released last weekend by D.V. Ramana and Silu Muduli of RBI:

Financial capability of an individual is the ability to use and manage financial products for current and future financial needs with adequate financial knowledge. This paper examines financial capability on four dimensions- financial management to meet current needs, future financial planning, financial products management, and financial knowledge using a sample of street vendors in Bhubaneswar, India.

A financial capability index for each individual in the sample has been calculated in a manner that satisfies monotonicity, anonymity, normalisation, uniformity, shortfall sensitivity and hiatus sensitivity to level axioms. We find that education, age, business experience, and daily turnover significantly affect the financial capability of an individual. Moreover, street vendors in regions with higher number of bank branches are found to have significantly higher financial capability.

These results are fairly intuitive as well..

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Using RCTs to Estimate Long-Run Impacts in Development Economics

Review paper on RCTs by Adrien Bouguen, Yue Huang, Michael Kremer, and Edward Miguel:

We assess evidence from randomized control trials (RCTs) on long-run economic productivity and living standards in poor countries. We first document that several studies estimate large positive long-run impacts, but that relatively few existing RCTs have been evaluated over the long-run. We next present evidence from a systematic survey of existing RCTs, with a focus on cash transfer and child health programs, and show that a meaningful subset can realistically be evaluated for long-run effects.

We discuss ways to bridge the gap between the burgeoning number of development RCTs and the limited number that have been followed up to date, including through new panel (longitudinal) data, improved participant tracking methods, alternative research designs, and access to administrative, remote sensing, and cell phone data.

We conclude that the rise of development economics RCTs since roughly 2000 provides a novel opportunity to generate high-quality evidence on the long-run drivers of living standards.

Hmm..

Post-Demonetisation patterns of deposits: a State-wise analysis

Nice bit of research by Tarun Kumar Saxena and Thoppil Bhargavan Sreejith of RBI.  It features in RBI’s monthly bulletin of Dec 2018.

The paper says deposits rose during demonetisation in most states and now people prefer savings deposits compared to term deposits. In terms of cash usage, only two states – Sikkim and Telangana – show a decline in its usage:

Shifts in ownership and tenor of deposits provide valuable insights into payment habits, saving propensities and liquidity preferences. This article has the vantage position of studying these patterns under the impact of a shock – in this case, demonetisation – and its backwash. This event appears to have produced a permanent shift in deposit behaviour with households’ preference shifting to savings deposits and away from term deposits. This suggests a premium on liquidity induced by the shock, partly incentivised by lower rates of returns on term deposits and alternative avenues of saving which combine the benefits of liquidity and returns. While the withdrawal of SBNs caused a shift in payment habits away from cash, this has proven to be short-lived and mean reversion became evident in 2017-18 itself. Only two states show a break from the central tendency, with a decline in cash dependency.

The results presented in this article draw from a census. They point to the fact that deposit and payment habits are inflexible across most states/ UTs in India and tend to return to steady state, even after large shocks. This has implications for banks’ deposit mobilisation strategies and business models.

Lots of tables and colorful graphs. One is noting RBI’s research bulletins is beginning to feature interesting research pieces. Keep up the tempo!

The role of transaction costs in Douglass North’s understanding of economic history

Nice paper by Rosolino Candela of George Mason University:

The purpose of this chapter is an attempt to reconstruct the evolution of North’s approach to understanding economic history. Underlying this evolution has been an increasing recognition of the role that transaction costs play in explaining the economic performance of different societies through time. I argue that, as a by-product of North’s emphasis on transaction costs throughout his scholarship, he transitioned from a neoclassical to an Austrian understanding of the process of economic change.

The implications of North’s growing emphasis on transactions costs throughout his career was a growing importance of other complementary features of economic theory, shared by Austrians, to explain processes of institutional change throughout economic history. These features of Austrian economic theory include: methodological subjectivism; competition and discovery under uncertainty; a dynamic conception of learning through time; and the role of ideology in structuring the patterns of meaning and purpose attached to human action.

 

Changing the way we teach monetary policy…

Øistein Røisland and Tommy Sveen of Norges Bank write this nice paper:

Monetary policy plays a central role in modern macroeconomics and many countries around the world has adopted inflation targeting as a guideline for policy. We emphasize and explain policy goals and then we assume that the central bank sets interest rates to ensure that these goals are met. We start with a simple model for a closed economy, where we briefly also discuss financial stability. We then expand the model and consider open economies. We develop the analytical results, but we focus on graphical discussions. Effects of various disturbances are analyzed using comparative statics.

They argue how traditional ISLM curve and its later variants hardly refer to the real world. We should instead start with policy goals of the central bank and assume central banks set interest rates to achieve these goals. Moreover, we also need to include financial stability and open economy considerations.

 

Insights from behavioral economics for India’s policy issues

Prof Ashima Goyal of IGIDR in this paper looks at behavioral constraints in policy and behavioral strategies for reform:

A long day of intense and enthusiastic debate among a Panchayat of wise elders has generated valuable insights. One of the learning points repeatedly touched on through the day is the importance of coordination across regulators, government departments and policies. Moreover, Bibek Debroy in his talk extended it to the citizen—how can the citizen help the government achieve its tasks.

Criticisms made, however, point to the question of why policy has not been able to deliver— why is it India has under-performed in so many dimensions? From the macroeconomic perspective, higher growth and some reduction in poverty has been associated with a lot of volatility. Growth has not yet crossed the threshold above which it becomes self-sustaining. Participants of this symposium were long associated with policy. There is an old saying that India has good economists but poor policy. Post liberalization, however, there is more optimism—it is agreed India has excellent potential but the question is when is it going to be realized?

It may be helpful to try a fresh approach. This year the Nobel Prize was given for behavioral economics. It is useful to examine behavioral constraints in policy making, and in achieving the required coordination. First we will apply psychological concepts to understand policy inadequacies, and then go on to see how general reforms or better coordination can be achieved using psychological trigger strategies.

Hmm.

Behavioral constraints:

• Over-reaction post 2008 crisis leading to high stimulus.
• Once bitten twice shy: The overreaction led to over cautiousness
• Wanting to do everything best before growth leads to losses in output.
• Copying from others like inflation targeting (ouch!) without looking at India specific issues.
• Interpreting rules too rigidly: Flexible Inflation targeting has become strict inflation targeting. Some discretion is important.
• Narrow vision where policymakers miss the connections in the economy
• Excess weight to foreign reputation and external risks
• Economists in Delhi are more pessimistic than those in Mumbai. (what about other cities?)
• Do not see any change by focusing on lower growth rates..
• Optimism and assuming 9% growth is ours..

Likewise there is a list of behavioral strategies for reform.

One may disagree with the arguments posed, but it is nevertheless an interesting and lighter way to assess Indian policy…

On money, debt, trust and central banking: Monetary Classic by Claudio Borio

This is a fabulous paper/speech by Claudio Borio of BIS. The kind which is a classic for monetary scholars.

This essay examines in detail the properties of a well functioning monetary system – defined as money plus the mechanisms to execute payments – in both the short and long run, drawing on both theory and the lessons from history. It stresses the importance of trust and of the institutions needed to secure it. Ensuring price and financial stability is critical to nurturing and maintaining that trust. In the process, the essay addresses several related questions, such as the relationship between money and debt, the viability of cryptocurrencies as money, money neutrality, and the nexus between monetary and financial stability. While the present monetary system, with central banks and a prudential apparatus at its core, can and must be improved, it still provides the best basis to build on.

There is a lot of history in the piece along with current and future challenges ahead of monetary policymakers. The reference list in the paper is also superb.

Black Market Prices in Japan during World War II.

Interesting paper by Masato Shizume of Bank of Japan:

This paper constructs a time series of data related to black-market prices of five goods (rice, sweet potatoes, potatoes, chicken eggs and sugar) during World War II (WWII) in Japan. It is the first attempt to capture the actual price fluctuation trends for individual products throughout the period during and after WWII. To this end, I have employed the hedonic approach, which is a methodology used to adjust for the quality of goods including the characteristics of counterparties and places of transaction in constructing the price data, to obtain estimates that are as unbiased as possible.

The data reveals that 1) black-market prices of these goods soared during WWII to post 40-80 percent inflation on a quarterly basis toward the end of the war, 2) by the end of the war, black-market prices had already increased by over 50 times (in the case of sweet potatoes) or 700 times (in the case of sugar) compared with 1934 levels, prior to wartime inflation, indicating more severe inflation during the war than after the war, 3) the most severe period of inflation varied by product, peaking during the war for rice and sugar and after the war for sweet potatoes, potatoes and chicken eggs, and 4) black-market prices were generally higher in urban areas than in rural areas.

Hmm..

Flight-to-safety and the Credit Crunch: A new history of the banking crisis in France during the Great Depression

Nice research by Patrice Baubeau , Eric Monnet, Angelo Riva  and Stefano  Ungaro.

They look at archival records of banks in France during Great Depression. They find that the impact was much severe than imagined:

Previous research has downplayed the role of banking panics and financial factors in the French Great Depression of the 1930s. Although scholars acknowledged that some banking failures occurred in France during the period 1930-1932, the common view of the absence of significant economic consequences has persisted. It results from the lack of statistics able to provide a comprehensive picture of the magnitude of banking panics, in the absence of banking regulation in France prior to 1941. The usual method to compute series of bank credit and deposits relied on the balance sheet of the four largest commercial banks – whose data were easily available – and to assume that those banks represented half of the banking sector. These large banks did not experience difficulties and their deposits did not decrease in 1930 and 1931.

Based on extensive archival research we have found the balance sheets of more than 400 hundred banks in interwar France. This finding gives a completely different view of the 1930-1931 banking crises. Whereas the four large commercial banks escaped the crisis, the remainder of the banking system experienced two dramatic waves of panic (end of 1930 and end of 1931), such that its deposits decreased by 40% between 1929 and 1931. The decrease in credit was even stronger (-44%). Banking panics were concentrated in 1930-1931. The decrease of banking activity that followed starting 1932 is fully explained by deflation.

Banking theory explains the mechanisms of bank runs, but it is silent on where deposits go when they are withdrawn from the banking system. Traditional monetary interpretations point to a drop in the money multiplier and in the money base, either because cash is hoarded or because deposits remain frozen in bankrupt banks. Our estimation of hoarded cash and frozen deposits show that they cannot account for the bulk of deposits that fled the banking system in 1930 and 1931.

Instead, most of these deposits went to savings institutions (Caisses d’Epargne) which collected deposits at a regulated interest rate and invested their assets in Treasury bonds. We characterize this phenomenon as a flight-to-safety. Because of capital inflows and the flight-to-safety from banks to non-banks, the total amount of deposits slightly increased in France from 1930 to 1932.

How can a country experience deflation and a decline of about 1/3 in real activity, whereas at the same time the money supply increases? The answer to this question lies in the dramatic decrease of credit. A credit crunch occurred because the institutions that received deposits during the banking panic – namely the saving institutions and the central bank – did not lend to the economy. New cash deposited with the savings institutions (Caisses d’épargne) was used directly to repay marketable public debt, which decreased between 1928 and 1933. 

The large banks which were not affected by the crisis deposited 25% of their assets with the central bank. The central bank increased very modestly its lending to the economy (both banks and non-banks) but it was dwarfed by the dramatic increase in gold reserves, the ultimate safe asset. Gold reserves doubled between 1929 and 1932. No financial institution replaced the banking system as a lender to the economy.

The highlighted bit suggests deposits lead to loans. But this has been disputed off late by several experts. Instead we now say loans lead to deposits.

Given this, a better way to say is there were limited business opportunities to lend to. So whether it is commercial banks or savings institutions, they either did not find lending opportunities or loan-seekers were not coming to these financial institutions….

China’s Monetary Policy Communication: Frameworks, Impact, and Recommendations

Nice paper by Michael McMahon, Alfred Schipke and Xiang Li. Apart from the communication channels used by PBOC, it gives one a sense of how PBOC conducts monetary policy:

Financial markets are eager for any signal of monetary policy from the People’s Bank of China (PBC). The importance of effective monetary policy communication will only increase as China continues to liberalize its financial system and open its economy. This paper discusses the country’s unique institutional setup and empirically analyzes the impact on financial markets of the PBC’s main communication channels, including a novel communication channel. The results suggest that there has been significant progress but that PBC communication is still evolving toward the level of other major economies. The paper recommends medium-term policy reforms and reforms that can be adopted quickly.

As a Mint piece argued, if central bank independence is so important for investors, how China continues to get funds…

UDAY Power Debt in Retrospect and Prospects: Analyzing the Efficiency Parameters

Nice and important paper in terms of figuring finances of India’s States. It is written by Amandeep Kaur and Lekha Chakraborty of NIPFP:

The Government of India launched the Ujwal DISCOM Assurance Yojana (UDAY), in November 2015, with an objective of “Power for All”. Under the UDAY
scheme, selected States agreed to convert 75 per cent of the DISCOM’s (State Power Distribution Companies) power debt into State government non-SLR bonds, priced at not more than 75 basis points above the prevailing cut-off yield rate of government security of 10-year maturity. At aggregate level, so far, around 86 per cent of  UDAY bonds have been issued – Rs. 2.32 lakh crores out of Rs. 2.69 lakh crores – across all UDAY States/UTs.

Our estimates reveal that the financial and operational efficiency parameters envisaged in UDAY tripartite MoUs – between DISCOMs, the
State Governments and the Ministry of Power, Government of India – have not been met by many States. Using UDAY portal data, we find that the average AT&C (Aggregate Technical and Commercial) losses that should have been 15% for all the participating states by 2018-19, presently, on average, stand at 25.41%. Yet another financial indicator, ACS-ARR gap (the gap between Average Cost and Average Revenue) has also widened for many UDAY participating states. The power tariff revisions have also not been implemented in the States -due to political economy reasons – and the operational parameters in our analysis indicate widening inefficiencies across States in power infrastructure.

Only a few states are doing their bit:

Using the UDAY portal data, the analysis revealed that it is crucial to move beyond the “fallacy of aggregation” of UDAY indicators and focus on the financial
and operational efficiency parameters of lagging states in meeting the UDAY targets. Our analysis based on the state-specific file sheets – StateHealth Cards – given in the state-wise dashboards, suggests that there are serious concerns in making the DISCOMs sustainable. We find that Gujarat, Karnataka, Himachal Pradesh and Telangana are the only States that have been performing well on majority of the financial and operational parameters of UDAY scheme.

As per the recent estimates based on the UDAY portal data accessed on October 2018, we find that financial and operational parameters of power infrastructure for majority of the States in India have shown a dismal picture and in turn raise questions about the efficacy of the UDAY scheme in materializing a turnaround in power sector.

Familiar story whenever we look at disaggregate picture..

How did research in finance start in Finland and become important overtime?

Interesting paper by Mika Vaihekoski of Bank of Finland. This is a paper which tells us how to go about writing research papers that matter and be counted in literature:

This paper reviews the first thirty years of finance research and education in Finland, starting with publication of the first dissertation in finance in 1977. That was also the year when the first department of finance was established in Finland – among the first in the Nordic countries. This review shows how Finnish financial education and research developed from a humble beginning to a level that brought international acclaim. This can be largely attributed to a number of talented and hard-working individuals but also to the decision for collaboration among the Finnish universities, as a means to overcome some of the problems of a small country.

 

Trust in financial services in Australia and last bank failure in Australia was in 1931…

I had written a  piece on how culture/ethics/trust is becoming one of the main talking points amidst central banks.

Philip Lowe, Governor Reserve Bank of Australia, joins in with this speech. Australia is going through its own sets of troubles with bankers found to be mis-selling financial products and services.

What I found more interesting was his mention of this bank failure in Australia:

Finance is all about trust. When a deposit is placed in a bank, we trust it will be repaid. We also trust financial institutions to invest our hard-earned savings for us. And we trust them to provide us with sound advice. Without this trust, the financial system cannot operate properly and the economy cannot prosper. As the first line of the Banking and Finance Oath says: ‘Trust is the foundation of my profession’.^[1] I encourage everybody in the finance sector to read this oath regularly and to live by it.

Australia’s banks have a strong record of being worthy of the trust that is placed in them to repay deposits. The last bank failure in Australia that resulted in a loss to depositors was almost 90 years ago, back in 1931, and it was a very small bank and depositors lost only a small fraction of their deposits.

This is a positive record that few countries can match. This strength was apparent during the financial crisis a decade ago and has served Australia well. The Australian banks are strongly capitalised and have considerable liquidity buffers. On the whole, they have also managed credit risk effectively, reporting few problem loans by global standards. This means that we can have a high level of trust in the ability of Australia’s banks to repay depositors. Indeed, our strong and stable banking system is one of the Australian economy’s strengths.

It is in other areas, though, where trust has been strained. It is clear that the behaviours highlighted by the Royal Commission have dented the community’s trust in parts of our financial sector.

It is quite a record really.

This paper further explains:

Only three banks failed during the 1930s ñ two small trading banks (the Primary Producers Bank and the Federal Deposit Bank) and the Government
Savings Bank of NSW. The Government Savings Bank was brought down by political turbulence as much as the economic conditions. While the
Commonwealth Bank provided some limited support to two of these banks, it was later criticised for not taking a more active role, particularly since two of the banks were solvent when they suspended payment.

In 1930, the Primary Producers Bank of Australia accounted for less than 0.5 per cent of Australian banksí deposits. Most of its customers were farmers, and
as the prices of primary produce fell the bank suffered a steady drain on its resources. Over the 18 months prior to the bankís closure, it lost 40 per cent of its
deposits.

In April 1931, the bank sought the assistance of the Commonwealth Bank in anticipation of a run following the suspension of the Government Savings Bank.
The Commonwealth Bank provided an unsecured overdraft of £100 000 and a loan of £295 000 secured by government bonds, a fixed deposit at another bank
and the bankís premises. The Primary Producers Bank actively sought amalgamation with the other trading banks and overseas financial groups. While
the Commonwealth Bank considered arranging joint action with the trading banks to avoid closure of the Primary Producers Bank, the other banks decided against the proposal. In the wind-up of the bank depositors were not quite fully paid, losing just 1.25 per cent of the value of their deposits (Royal Commission into the Monetary and Banking Systems 1937).

Need to read more amd more about different banking systems across the world….

What are we learning about Artificial Intelligence in Financial Services?

Federal Reserve Governor Lael Brainard takes us through this interesting fascinating topic.

My focus today is the branch of artificial intelligence known as machine learning, which is the basis of many recent advances and commercial applications.² Modern machine learning applies and refines, or “trains,” a series of algorithms on a large data set by optimizing iteratively as it learns in order to identify patterns and make predictions for new data.³Machine learning essentially imposes much less structure on how data is interpreted compared to conventional approaches in which programmers impose ex ante rule sets to make decisions.

The three key components of AI–algorithms, processing power, and big data–are all increasingly accessible. Due to an early commitment to open-source principles, AI algorithms from some of the largest companies are available to even nascent startups.⁴ As for processing power, continuing innovation by public cloud providers means that with only a laptop and a credit card, it is possible to tap into some of the world’s most powerful computing systems by paying only for usage time, without having to build out substantial hardware infrastructure. Vendors have made it easy to use these tools for even small businesses and non-technology firms, including in the financial sector. Public cloud companies provide access to pre-trained AI models via developer-friendly application programming interfaces or even “drop and drag” tools for creating sophisticated AI models.⁵ Most notably, the world is creating data to feed those models at an ever-increasing rate. Whereas in 2013 it was estimated that 90 percent of the world’s data had been created in the prior two years, by 2016, IBM estimated that 90 percent of global data had been created in the prior year alone.⁶

The pace and ubiquity of AI innovation have surprised even experts. The best AI result on a popular image recognition challenge improved from a 26 percent error rate to 3.5 percent in just four years. That is lower than the human error rate of 5 percent.⁷ In one study, a combination AI-human approach brought the error rate down even further–to 0.5 percent.

So it is no surprise that many financial services firms are devoting so much money, attention, and time to developing and using AI approaches. Broadly, there is particular interest in at least five capabilities.⁸ First, firms view AI approaches as potentially having superior ability for pattern recognition, such as identifying relationships among variables that are not intuitive or not revealed by more traditional modeling. Second, firms see potential cost efficiencies where AI approaches may be able to arrive at outcomes more cheaply with no reduction in performance. Third, AI approaches might have greater accuracy in processing because of their greater automation compared to approaches that have more human input and higher “operator error.” Fourth, firms may see better predictive power with AI compared to more traditional approaches–for instance, in improving investment performance or expanding credit access. Finally, AI approaches are better than conventional approaches at accommodating very large and less-structured data sets and processing those data more efficiently and effectively. Some machine learning approaches can be “let loose” on data sets to identify patterns or develop predictions without the need to specify a functional form ex ante.

What do those capabilities mean in terms of how we bank? The Financial Stability Board highlighted four areas where AI could impact banking.⁹ First, customer-facing uses could combine expanded consumer data sets with new algorithms to assess credit quality or price insurance policies. And chatbots could provide help and even financial advice to consumers, saving them the waiting time to speak with a live operator. Second, there is the potential for strengthening back-office operations, such as advanced models for capital optimization, model risk management, stress testing, and market impact analysis. Third, AI approaches could be applied to trading and investment strategies, from identifying new signals on price movements to using past trading behavior to anticipate a client’s next order. Finally, there are likely to be AI advancements in compliance and risk mitigation by banks. AI solutions are already being used by some firms in areas like fraud detection, capital optimization, and portfolio management.

Hmm…

One believes that sooner than later we will either have technologists in top management at central banks (even banks) or the top management will have to undergo rigorous tech training. This is no more science fiction but day light reality.

IMF building case for Central Bank Digital Currencies (and mentions hundis too!)

Christine Lagarde in this speech discusses discusses pros and cons of issuing a central bank digital currency.

But before discussing CBDC, it was really surprising to see IMF chief mentioning hundis:

Let me begin with the big issue on the table today—the changing nature of money. When commerce was local, centered around the town square, money in the form of tokens—metal coins—was sufficient. And it was efficient.

The exchange of coins from one hand to another settled transactions. So long as the coins were valid—determined by glancing, scratching, or even biting into them—it did not matter which hands held them. But as commerce moved to ships, like those that passed through Singapore, and covered increasingly greater distances, carrying coins became expensive, risky, and cumbersome.

Chinese paper money—introduced in the 9^th century—helped, but not enough. Innovation produced bills of exchange—pieces of paper allowing merchants with a bank account in their home city to draw money from a bank at their destination.

The Arabs called these Sakks, the origin of our word “check” today. These checks, and the banks that went along with them, spread around the world, spearheaded by the Italian bankers and merchants of the Renaissance. Other examples are the Chinese Shansi and Indian Hundi bills.

Suddenly, it mattered whom you dealt with. Was this Persian merchant the rightful owner of that bill? Was the bill trustworthy? Was that Shanxi bank going to accept it? Trust became essential—and the state became the guarantor of that trust, by offering liquidity backstops, and supervision.

Why is this brief tour of history relevant? Because the fintech revolution questions the two forms of money we just discussed—coins and commercial bank deposits. And it questions the role of the state in providing money.

Hundis has long been forgotten by researchers in India barring those history folks. Nice to see Lagarde mentioning hundis along with Sakks and Shansi..

Now to CBDC:

How does Inflation in Indian States differ with the national average?

Nice article by Sujata Kundu, Vimal Kishore and Binod B. Bhoi of RBI. It is released in RBI Bulletin for the month Nov-2018.

They look at how inflation is behaving in India’s States:

An analysis of the regional inflation dynamics in India reveals the presence of wide dispersion in inflation across states, largely driven by food price inflation. State level inflation tends to converge to the national average over time, however, validating the choice of national level consumer price inflation as the nominal anchor for monetary policy in India.

Which state has the highest average inflation and volatility? Interestingly, Southern States have higher average inflation (6.8%) compared to others:

Notably, all the southern states had higher average inflation than northern states like Punjab, Haryana, Uttar Pradesh and Uttarakhand as well as states in other regions like Maharashtra and Madhya Pradesh. Bihar recorded the highest inflation of 16.1 per cent (November 2013), while Chhattisgarh recorded the
lowest inflation level of (-) 2.3 per cent (June 2017) as against the national-level maximum of 11.5 per cent (November 2013) and minimum of 1.5 per cent
(June 2017). 

Over this period, inflation and inflation volatility did not exhibit any noteworthy co-movement, which is in contrast with the two-way causality posited in the
literature . In fact, when inflation averaged a high of 10.0 per cent in 2012-13, its volatility was at the lowest in the period of study at 0.5 per cent; volatility rose to 1.2 per cent when average inflation was at its lowest level of 3.6 per cent in 2017-18 (Chart 4a). This relationship alters dramatically, however, in the regional setting.

Unlike the all-India pattern, state-level inflation and inflation volatility co-moved during 2012-13 to 2017-18 (Chart 4b). Another interesting observation is that the states/regions that experienced high average inflation (e.g., Bihar, Chhattisgarh, Odisha and West Bengal) also recorded high volatility in inflation.

Much more in the short research paper with graphs and tables. RBI should release more and more of such type research.

Paradise lost? A brief history of DSGE macroeconomics

Gulan Adam of Bank of Finland provides a brief overview in this paper:

Since the Global Financial Crisis, academic economists and policymakers have had to deal with uncomfortable questions about the quality of their models and the state of macroeconomics as a profession. This note offers a summary of this discussion, focusing on the Dynamic Stochastic General Equilibrium (DSGE) framework and its underpinnings. This class of models reflects both theoretical advances and perennial modeling challenges.

While DSGE modeling developed in times of scarce micro data and limited computational resources, it has much room for improvement given progress along these dimensions and advances in other branches of economics. Key tasks on the to-do-list for model improvement include the modeling on the financial sector, departures from the representative agent and rationality, as well as clarification of the empirical relevance of the Lucas critique. The framework is likely to remain a major research and policy tool, although its limitations call for greater robustness, validation and open recognition of uncertainty in drawing real-life quantitative conclusions.

We need more and more of such papers to help demystify the acronym DSGE…

How German women obtained the right to vote 100 years ago?

Women won the rights to vote in Germany on 12 Nov 1918.

Here is brief history of how it happened.

50 years of Gunnar Myrdal’s Asian Drama: History of Indian economy since 1968…

Swedish economist Gunnar Myrdal published his book – Asian Drama- 50 years ago in 1968.

Prof Kaushik Basu reviews India’s economic history since 1968 in this paper:

This paper is a short history of the Indian economy since 1968. India today is a changed country from what it was half a century ago, when Myrdal published his Asian Drama. The stranglehold of low growth has been broken, its population below the poverty line has fallen markedly, and India has joined the pantheon of major players globally. This paper analyses the economic policies and the politics behind this transformation; and uses that as a backdrop to take
stock of the huge challenges that lie ahead.

Here is another piece from Prof Ravi Kanbur:

Gunnar Myrdal’s “Asian Drama” was published 50 years ago. On the face of it, the book, framed in terms of the realities of an economically stagnant Asia, appears to have little to offer the modern development economist. This column argues, however, that the issues Myrdal raised are fundamental ones not only for development but for our discipline of economics and for the broader terrain of political economy.

Implications of e-krona project on different aspects of Swedish monetary and banking system

Superb research by team of Riksbank economists.

The Riksbank is investigating the possibility and consequences of introducing a Swedish central bank digital currency, a so-called e-krona. The latest issue of our journal Economic Review is a special theme issue discussing the e-krona from different perspectives. What is the role of the central bank in the payments market? What might the demand for an e-krona be? What consequences will this have for the banks? How will rate-setting be affected, and what further effects might the e-krona have for monetary policy and economic developments in the long run?

It includes following articles:

• Why did the Riksbank receive a banknote monopoly? 
• What is money and what type of money would an e-krona be? 
• Implications of an e-krona for the Riksbank’s framework for implementing monetary policy
• The e-krona and the macroeconomy
• How many e-kronas are needed for payments?
• When a central bank digital currency meets private money: effects of an e-krona on banks

Must read for those interested in digital money and even money in general…