Inflation Stories of the Week (January 31, 2014)

1. Rajan Signals India Inflation Target Amid Vote Tension (Bloomberg): India central bank Governor Raghuram Rajan may attempt to make inflation the bank's primary priority. Rajan says, "If the government policies in aggregate prove to be expansionary, we will have to adjust policies ourselves to meet the overall disinflationary process. We can’t throw up our hands in some sense and say there is nothing we can do because of the fiscal dominance."

2. Hungary Rate-Cut Resolve Challenged by Investors as Forint Drops (Bloomberg): Inflation in Hungary is at its lowest since 1970. Central banks in Turkey and South Africa are raising rates to try and stop falling currencies, but the Hungarian central bank faces a challenge because monetary easing is more appropriate to its inflation and growth conditions.

3. Inflation in Euro Zone Falls, and a 12% Jobless Rate Doesn’t Budge (NYT): The 0.7 percent inflation rate may have surprised the ECB.

4. Japan’s Inflation Accelerates as Abe Seeks Wage Gains (Bloomberg): Japan's inflation has inched up, but the real test will come at the annual wage talks in April. Prime Minister Shinzo Abe has met five times since September with business and union leaders to encourage them to raise salaries, which have risen slower than prices.

Inflation Stories of the Week Archive

"Forecasting Profitability": A New Study of Uncertainty and Investment

I hope macroeconomists don't overlook this new paper from the development literature: Forecasting Profitability, an NBER working paper by Mark Rosenzweig and Christopher R. Udry, provides an extremely concrete and clean example of how uncertainty can matter for an economy.  (They don't actually use the word uncertainty, because it's apparently not as much of a buzzword in other fields of economics right now as it is in macro.)

The uncertainty studied in this paper concerns the weather. The authors note that "in India the India Meteorological Department (IMD) has been issuing annual forecasts of the monsoon across the subcontinent since 1895, and it is widely reported in the Indian media that farmers’ livelihoods depend upon the accuracy of the forecast." From the introduction [emphasis added]:

"It is well‐established that agricultural profits in developing countries depend strongly on
weather realizations. It is similarly well‐known from the development economics literature that farmers without access to good insurance markets act conservatively, investing less on their farms and choosing crop mixes and cultivation techniques that reduce the volatility of farm profits at the expense of lower expected profits. Economists have focused valuable attention on policies and programs that can provide improved ex post mechanisms for dealing with the consequences of this variability. For example, innovations in insurance can spread risk across broader populations, or improved credit or savings institutions can permit more effective consumption‐smoothing over time...

Economists, however, have paid little attention to directly improving farmers’ capacity to deal
with weather fluctuations by improving the accuracy of forecasts of inter‐annual variations in weather. Like actuarially fair insurance, a perfectly accurate forecast of this year’s weather pattern, provided before a farmer makes his or her production decisions for the season, eliminates weather risk. However, a perfect forecast permits the farmer to make optimal production choices conditional on the realized weather and thus achieve higher profits on average compared with a risk‐neutral or perfectly‐insured farmer. The profit and welfare gains associated with improvements in the accuracy of long‐range forecasts (forecasts that cover, for example, an entire growing season) are potentially enormous, given the tremendous variability in profits and optimal investment choices across weather realizations."

Here's a bit about the methodology and results:

"In this paper we used newly‐available panel data on farmers in India to estimate how the
returns to planting‐stage investments vary by rainfall realizations using an IV strategy in which the Indian forecast of monsoon rainfall serves as the main instrument. We show that the Indian forecasts significantly affect farmer investment decisions and that these responses account for a substantial fraction of the inter‐annual variability in planting‐stage investments, that the skill of the forecasts vary across areas of India, and that farmers respond more strongly to the forecast where there is more forecast skill and not at all when there is no skill. Our profit‐function estimates indicate that Indian farmers on average under‐invest, by a factor of three, when we compare actual levels of investments with the optimal investment level that maximizes expected profits over the full distribution of rainfall realizations.

We also used our estimates to quantify how farmers’ responses to the forecast affect both the
level and variability in profits... These indicated that farmer’s use of the forecasts increased average profit levels but also increased profit variability compared with farmers without access to forecasts. Indeed, based on the actual behavior of the farmers, our estimates indicated that they do better than farmers who would undertake optimal, unconstrained investments but have no forecasts when rainfall realizations are high, but worse under adverse rainfall conditions. Finally, we also assessed how profit levels would increase in the future as forecast skill increases under current climate conditions and under conditions predicted by climate models. These exercises indicate that even modest skill improvements would substantially increase average profits, and slightly more so in a warmed climate."

Obviously, weather realizations affect farmers' livelihood. But the precision with which farmers can predict the weather ahead of time also affects their livelihood: less precision (more uncertainty) reduces investment and reduces expected profits. The above allusion to "a warmed climate" is an example of what an "uncertainty shock" could be in this context. If climate change increases weather volatility, then without an improvement in forecast skill, there would be more uncertainty. The model in the paper can get at quantifying the impact of that uncertainty shock. The paper also mentions a new government policy aimed at improving the economy through reducing uncertainty. Monsoon Mission, launched in India in 2012, has a five-year budget of $48 million to support research on improving weather forecasting ability.

Raghuram Rajan is Not Paul Volcker

Raghuram Rajan will take over leadership of the Reserve Bank of India (RBI) on September 4. The BBC lists some of the challenges facing the Indian economy, including a large current account deficit, weak rupee, the slowest growth in a decade (around 5%), and inequality, adding, "Many believe that the single biggest failure of the government's economic policies in recent years has been the inability to control inflation in general and food prices in particular."

It's clear that Rajan will have his work cut out for him, but what kind of work will that be? 

"The monetary situation is such that he may be forced to act as India’s Paul Volcker, hiking up rates and perhaps even orchestrating a recession to get the currency and inflation under control," writes Dylan Matthews. Matthews notes that "By law, India’s central bank doesn’t have much political independence, as Rajan serves at the pleasure of the government and can be sacked at any time. That could deter him from making tough moves against inflation that could have unpopular implications for growth. But Subramanian thinks he’ll have a great deal of flexibility in practice, even if the opposition Bharatiya Janata Party comes to power again."

There is a tendency to want to frame the challenges of the Indian economy in terms of a power struggle between monetary and fiscal authorities-- an "unseemly battle of wits over interest rates," according to Rajrishi Singhal at Bloomberg.  Singhal describes how the Finance Ministry has piled pressure on Rajan's predecessor, RBI Governor Duvvuri Subbarao, to keep rates low. The idea is that, if only the new Governor can stand up to "bullying" and raise rates, then inflation and the rupee can be stabilized. But India in 2013 is not the U.S. in 1979, and Raghuram Rajan need not imitate Paul Volcker.

A central banker's role in India is much different than a central banker's role in the United States or Europe. Monetary policy, remember, is ultimately based on frictions. Prices and inflation are nominal variables. In a frictionless economy, there is no role for monetary policy. It is because of certain frictions that monetary policy can have short-run effects, and these frictions provide the justification for using monetary policy to stabilize economic fluctuations over the business cycle. The optimal monetary policy depends on the nature and magnitude of these frictions. Sticky prices and sticky information are the two categories of frictions most used in the analysis of monetary policy. Both have similar implications for how monetary policy should generally work.

The theory behind the Taylor rule is based on the sticky price friction. The rule recommends a relatively high interest rate or “tight” policy when inflation or employment is relatively high, and a relatively low interest rate in the opposite scenario. According to the Taylor rule, India's policy rates are currently too low. As Ashok Rao writes (in a very excellent post), "A healthy Taylor rule requires an accurate estimate of the output gap which is founded on long-run trend growth. “Trend” growth is a useless concept in countries like India and China, whose growth rates have both a high mean and variance."

But there may be a more fundamental reason why the Taylor rule is not suitable for India. The Taylor rule is based on the sticky price friction, which may not be the dominant friction. Amartya Lahiri suggests that the dominant friction is asset market segmentation (emphasis added).

A well-known feature of the Indian economy is that access to asset markets and instruments is extremely limited. About 140 million households in India do not have access to any formal banking at all. Consequently, less than half of all individuals have access to any formal financial services...It is thus abundantly clear that there is endemic and widespread segmentation in asset markets in India with only a small subset of India having access to formal asset markets. But curiously, discussions about monetary policy in India are completely divorced from this asset market segmentation."

How does asset market segmentation impact the monetary policy calculus? In this case the central bank needs to use monetary policy to provide insurance to those that are absent from these markets. This policy imperative can naturally imply very different monetary policy responses relative to when prices are sticky.

Rajesh Singh, Amartya Lahiri, and Carlos Vegh study optimal monetary policy in environments with segmented asset markets. As Lahiri summarizes,

Intuitively, the role of policy under this friction is to protect households that are excluded from asset markets from excessive fluctuations in their consumption levels. When output is high, consumption of these households tends to rise due to (a) higher income; and (b) higher real money balances as the exchange rate tends to appreciate. By expanding money supply, the central bank can inflate away some of the increase in real balances and thereby moderate the rise in consumption. This procyclicality of the optimal monetary policy is clearly at odds with the Taylor rule prescription that monetary policy should be countercyclical.

The authors also find that asset market segmentation has surprising effects on optimal exchange rate regimes (effectively the opposite of the Mudellian model). They come down in favor of targeting monetary aggregates instead of targeting the exchange rate. The model of Singh et al. is admittedly very stylized and I have found no existing tests of its empirical implications. So I am certainly not actually recommending that Rajan rush to lower interest rates. Nor am I suggesting that Rao's proposal of a rule-based exchange rate policy should be off the table.

Rather, I just intend to highlight the topsy-turvy theoretical results that can arise when we alter the foundations of our models; in particular, when we acknowledge lack of financial inclusion as a significant friction. I also believe that an important role for Rajan, perhaps more important than any decision about interest rates, will be in reforming the financial system and promoting financial inclusion. I am very optimistic on this front. The Financial Times reports that "economists who know Mr Rajan well say helping hundreds of millions of Indians get access to efficient financial services is close to his heart." In 2008, he wrote "A Hundred Small Steps," a report on financial sector reforms. I am most impressed by his inclusion in Chapter 3, "Broadening Access to Finance," of this chart, which shows the interest rates actually paid by people in each income quartile.

It appears that he is quite sensitive to the severity of asset market segmentation in India and to the fact that interest rate movements are not evenly transmitted across all segments of the population.