Interacting Expectations: A Study of Short-Term and Long-Term Inflation Forecasting in India

Abstract

Inflation is a psychological phenomenon that affects people's purchasing decisions, with the US economy experiencing an 8.5% inflation rate in 2022. People's beliefs about inflation are based on emotions rather than facts, making them illogical. People may change their behavior in response to inflation by looking for sales, trading down, putting off purchases, buying in smaller amounts, or buying in larger amounts due to bulk purchases. Discount stores like Costco or Walmart are often used to attract customers who are hesitant to pay more for their goods.

Businesses react to inflation differently based on their classification, with lower-tier or value brands replacing premium brands. Store brands like CVS and Target often see sales rise during inflation periods. For example, Costco offers petrol discounts to attract customers who are hesitant to pay more.

Inflationary expectations play a significant role in determining actual inflation outcomes in different economies. Milton Friedman's work in the 1960s laid the groundwork for incorporating individual expectations into macroeconomic models, guiding future research. His ideas inspired a generation of economists to examine how expectations affect macroeconomic models, asset prices, and money movement in the economy.

Inflation expectations are crucial for maintaining economic stability, and their formation and holding in place vary depending on the economic theory and real-world situation. The rational expectations hypothesis, proposed by John Muth in 1961, suggests that people make expectations based on all available information. Behavioral models and surveys are used to guess inflation based on perceived prices. Central banks worldwide recognize the importance of expectations in maintaining economic stability.

Emerging market economies, such as India, face challenges such as inequality, structural unemployment, and weak institutions. Globalization has also exacerbated inequality and inflation. Inflation is both a sign of and a cause of larger changes in the economy, and maintaining stable prices is essential for building investor trust and encouraging long-term growth.

Policymakers can better manage inflation and predict how people will act by understanding how agents like consumers, producers, employers, and employees form expectations. The Phillips Curve, the Phillips Curve-augmented form, the New Keynesian Curve, and the Hybrid New Keynesian Curve all use inflation expectations as a key factor in price behavior.

As the world's economies become more connected, policymakers must understand and manage expectations to ensure long-term economic stability. In conclusion, including inflationary expectations in the study of inflation changes over time is essential for understanding and managing inflation.

This study examines how inflation expectations explain actual inflation trends in India. Three groups of hypotheses are tested: the link between actual inflation and expectations for three months from now, the link between actual inflation and expectations for the next year, and how expectations change over time. The Reserve Bank of India collected time-series data on household inflation expectations to determine if they are adaptive. The data was tested for stationarity and a unit root to ensure accurate regression or trend analysis.

Inflation expectations are active forces that influence economic behavior and policy responses, rather than being passive reflections of expected price movements. They are crucial in the theoretical framework established by Kydland and Prescott (1977) and Barro and Gordon (1983), especially in emerging market economies. Central banks in these economies aim to maintain a stable rate of inflation and lessen price volatility, which cannot be achieved without taking economic agents' expectations into account.

Economic theory has long recognized the critical role expectations play in inflation dynamics, with Milton Friedman's adaptive expectations hypothesis signaling a paradigm shift. Bernanke and Mishkin (1997) emphasize the importance of inflation expectations in determining the efficacy and legitimacy of monetary policy, particularly in emerging market economies where structural vulnerabilities make anchoring expectations more difficult.

Inflation expectations have been measured across various economies using various methods, including the rational expectations hypothesis, behavioral models, survey-based approaches, and indicator-based approaches. Central banks have made efforts to understand the pivotal role expectations play in determining macroeconomic outcomes. Jan Marc Berk's research in the Netherlands used consumer surveys to measure inflation expectations using the Carlson-Parkin probability approach. The study aims to examine the impact of inflation expectations on actual inflation in the Indian economy using the Reserve Bank of India's quarterly Inflation Expectations Survey of Households (IESH). The survey collects data every three months from 12 cities, including the four biggest cities, and asks about 4,000 households' expectations for price changes over the next three months and one year. The survey collects both qualitative and quantitative data, focusing on how respondents see general and specific price trends over the short and medium term. The study found that Indian households do not all consume the same way, due to differences in culture, religion, education, lifestyle, and local economic conditions. This makes a one-size-fits-all monetary policy approach useless in a country as diverse as India.

The Reserve Bank of India (RBI) has consistently improved the household inflation expectation survey to make it more accurate and useful. Changes to the sample size, sampling framework, and forecast horizon are part of these changes, aiming to make estimates more detailed and specific. The 2009 RBI Internal Group Report praised the success of the survey project and suggested making the data public on the RBI's official website to encourage openness, raise public awareness, and build trust in the monetary policy framework.
Adding inflation expectations to macroeconomic analysis has been helpful in understanding how people's perceptions affect their economic behavior. The RBI's household survey provides timely and useful information, allowing policymakers to better understand how people form inflation expectations and how to change them. By focusing on factors that cause expectations, such as recent price trends, news stories, and local consumption patterns, policymakers can create measures that better anchor expectations and help keep actual inflation from going up too much. Aligning policy changes with the main factors that affect household expectations can help close the gap between what people expect and what actually happens with inflation, making monetary policy more credible and strengthening its spread.

The Reserve Bank of India (RBI) conducted a quarterly Inflation Expectations Survey of Households from March 2009 to December 2019. The data points from the survey show that inflation expectations closely follow actual inflation trends, providing a strong basis for understanding and predicting price levels in the Indian economy. However, there is still a consistent gap between actual inflation and expected inflation, with expectations generally being higher. This difference highlights the importance of studying the factors that affect how households expect inflation to change. Targeted policy changes that fill in these gaps can make inflation predictions more accurate and improve monetary policy. The graph shows that the three variables move together strongly, providing a strong basis for understanding and predicting price levels in the Indian economy.

A study examining the impact of inflation expectations on actual inflation in India found that both variables, expectations three months ahead and expectations one year ahead, explained a significant part of the change in actual inflation. The regression analysis showed that people base their decisions about current and future prices on their expectations, both those they have recently and those they have in the future. The results support the theoretical literature that inflation expectations play a big role in determining actual inflation outcomes.

The correlation matrix for the three variables showed a strong linear relationship between actual inflation and expectations. The correlation coefficient between inflation that has already happened and expectations three months ahead is 0.984, and there is a 0.960 correlation between actual inflation and expectations for one year from now. This behavior gives policymakers important information about how inflation works and how monetary policy spreads.

In conclusion, the results show that inflation expectations have a real effect on inflation, making it even more important to include expectation management as a key part of India's inflation-targeting strategies. The regression model can be considered statistically sound and a good way to look at the link between inflation expectations and actual inflation in India.

The regression model reveals that inflation expectations three months ahead and one year ahead can explain the actual inflation rate reported by survey respondents. The model accounts for a large part of the total sum of squares, with a low residual sum of squares. The F-statistic's significance value is 0.000, indicating that the two expectation variables can be trusted to predict the actual inflation rate. However, more research is needed to determine the importance and strength of each predictor on its own.

The correlation matrix between actual inflation and expectations for the next three months shows a strong positive linear relationship, with a correlation coefficient of 0.984. This results support the behavioral idea that people base their expectations on short-term price trends, which then affects how they think about current inflation.

The regression results are statistically strong and reliable for the sample, showing that about 96.9% of the total change in actual inflation can be explained by what people thought prices would be three months from now. The adjusted R-squared stays high at 96.8%, and the mean square residual (MSR) is low at 0.327, indicating a small unexplained variance.

In conclusion, the regression model is a strong and reliable way to understand how short-term inflation expectations and actual inflation are related. The regression model explains the actual inflation rate based on survey respondents' predictions of inflation over the next three months. The model is statistically significant at the 5% level, indicating that short-term inflation expectations can predict the actual inflation rate. The results show that for every 1-unit rise in short-term inflation expectations, the actual inflation rate rises by about 0.984 units, demonstrating the strong relationship between short-term expectations and actual inflation outcomes. These results support the idea that short-term expectations are reliable inputs for predicting inflation outcomes.