What Goes Into Determining the 'Fair' Value of the Rupee?

A considerable debate has emerged over the value of the Indian rupee in recent months. Some economists argue that its recent depreciation against the dollar is justified, claiming that the rupee was overvalued, and that this correction will boost India’s exports. Others warn that the weakening currency could fuel inflation and overheat the economy. In February, the rupee fell to over 87 per dollar.

Exchange rates play a crucial role in a country’s economic stability, influencing trade, investment and inflation. But how do we determine if a currency’s value is “fair”? This is where equilibrium exchange rate models come in. In their latest research paper, “A Suite of Approaches for Estimating Equilibrium Exchange Rates for India 2.0”, former Reserve Bank of India (RBI) Deputy Governor Michael Debabrata Patra and his co-authors explore various methods to estimate the rupee’s fair value based on economic fundamentals.

Building on their previous work, the authors expand the range of models used to assess equilibrium exchange rates. These models help policymakers and economists determine whether the rupee is overvalued or undervalued—insights that have direct implications for India’s trade competitiveness, inflation and financial stability.

Estimating the Equilibrium

One of the key approaches discussed in the paper is the capital enhanced equilibrium exchange rate (CHEER) method. This method helps estimate the fair value of the rupee by looking at two important economic factors: price differentials or inflation differences between India and other countries, and interest rate differentials between India and the US.

The researchers use an equation to determine India’s nominal effective exchange rate (NEER)—a measure of the rupee’s value against a basket of 40 trading partner currencies. They also estimate the rupee’s bilateral exchange rate with the dollar.

To ensure accuracy, the authors transform the exchange rate and price data into logarithmic form—a statistical method that stabilises variations. They also use quarterly data from 2004 to 2024 and employ a technique called vector error correction modelling (VECM) to identify the long-term relationship between price levels, interest rates and exchange rate.

Their findings confirm an expected pattern.

If prices in India rise faster than in the US, the rupee depreciates because Indian exports become more expensive and less competitive. Meanwhile, the rupee appreciates when India’s interest rates are significantly higher than US rates, as foreign investors are drawn to India’s higher returns, leading to capital inflows.

The research paper finds that in the long run, India’s NEER and the rupee-dollar exchange rate largely align with their equilibrium levels, except during period of economic shocks like the 2013 taper tantrum.

In the short run, however, exchange rates tend to be influenced by their own past values or lags, meaning that temporary fluctuations may not always reflect fundamental economic conditions. The error correction term (ECT) in their model, which measures how quickly exchange rates return to equilibrium after a shock, is found to be statistically significant. This confirms that the models used are stable and reliable for exchange rate estimation.

Productivity is Key

Another approach discussed in the paper is the desired equilibrium exchange rate (DEER) method. Unlike the CHEER approach, which focuses on price and interest rate differentials, the DEER method links the rupee’s value to India’s growth and current-account balance (CAB)—a measure of the country’s trade and financial flows.

To estimate the DEER, the authors use an autoregressive distributed lag (ARDL) model, which captures both short-term fluctuations and long-term trends from 2004 to 2024. This model incorporates key economic variables such as the real effective exchange rate (REER)—NEER adjusted for inflation, India’s real GDP and global GDP—proxied by the combined GDP of G20 nations. It also accounts for shocks like the 2008 global financial crisis (GFC) and the taper tantrum using dummy variables.

By applying a statistical method that isolates long-term trends, the researchers estimate how these factors influence the rupee’s equilibrium exchange rate.

Their findings suggest that higher domestic GDP worsens India’s CAB, likely due to increased imports. In contrast, higher global GDP improves India’s CAB, as stronger global demand boost exports. However, a stronger rupee due to higher domestic GDP is associated with an improved CAB, possibly due to productivity gains that help maintain export competitiveness despite currency appreciation.

This suggests that a stronger rupee does not necessarily harm India’s trade balance if productivity continues to improve.

Finding the Real Rate

To assess misalignment, the study compares the DEER with the REER—the exchange rate that matches India’s economic fundamentals with the actual value of the rupee compared to its trading partners. If the observed REER is higher than DEER, it means the rupee is stronger than it should be. Conversely, the rupee is undervalued if the observed REER is lower than the DEER. The study considers different CAB targets to assess the level of equilibrium real exchange rate consistent with a specific policy that is relevant for external stability.

Towards the end, the study also examines the medium- and long-term factors affecting REER using the NATREX model. In the medium run, higher consumption demand or domestic productivity leads to REER appreciation. However, their long-term effects differ—higher consumption results in foreign debt accumulation and eventual REER depreciation, while productivity growth strengthens the current account, leading to long-term REER appreciation.

Empirical findings suggest that in 2023–24, India’s REER was broadly aligned with long-term fundamentals but slightly undervalued in the medium run, indicating room for appreciation.

Overall, this study provides a thorough analysis of India’s equilibrium exchange rate using multiple frameworks, offering valuable insights into exchange rate dynamics. By incorporating both medium- and long-term perspectives, it highlights the nuanced relationship between domestic productivity, external debt, and global economic conditions. However, the findings remain sensitive to model assumptions and parameter choices, underscoring the inherent complexity of exchange rate assessments.

While the study presents a useful toolkit for policy discussions, future research could refine these estimates with evolving macroeconomic conditions and alternative modelling approaches.