Econometric model to predict USD INR exchange rate Economic Essay (2023)

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The purpose of this article is to build a model that successfully predicts USD/INR movement in the medium/long term. Much research and analysis has already been done in the field of currency forecasting as it is an area of ​​interest for scientists, business houses, investors and governments. While the researchers also tried the random walk model and the fundamental asset pricing model, this paper attempts to predict the exchange rate based on macroeconomic variables using statistical techniques such as correlation analysis and stepwise multiple regression analysis.

The analysis was conducted on quarterly data for various Indian and US economic indicators from 1996 to the second quarter of 2012.

Data from Q1 1996 to Q4 2010 (60 quarters) was used to build and train the model, and data from Q1 2011 to Q2 2012 (6 quarters) was used for validation (out-of-sample control accuracy) of the model.

The model that emerged from the research predicts the exchange rate z

70% accuracy within +/-1.5% of the actual exchange rate

Accuracy 53% and range +/- 1.0% of the actual exchange rate

Accuracy 44% and range +/- 0.75% of the actual exchange rate

Accuracy of 30% and a range of +/- 0.50 of the actual exchange rate

Accuracy of 19% and a range of +/- 0.25 of the actual exchange rate

Since the model is based on macroeconomic variables and does not account for microeconomic variables, given the time frame, the model does not account for the impact of microeconomic factors, which can create a margin of error in the forecast.

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It has been found that the model is unable to predict the exchange rate for a given period within the assumed residual range; it is likely that some variables not accounted for in the regression equation should be included. So there is more room to expand this analysis and examine these time periods in depth and include those variables that will add more flavor to the results and narrow the areas where the model cannot track the true price.

The main data sources were - IMF and IFS, US organizations like CSO, BEA, BLS and Reserve Bank of India


This thesis would not have been accomplished without the guidance and assistance of several people who contributed in one way or another and provided valuable assistance in the preparation and completion of this research.

First of all, I am immensely grateful to Dr. Sunil Ashra, Associate Professor, Economics, Management Development Institute, whose sincerity and encouragement I will never forget. Mr. Prashant Dabas, Senior CEO of R&A, WNS (Holdings) Limited, India, was an inspiration to me as I overcame all obstacles in completing this research work.

The staff of the MDI library especially for customizing to our requirement to help for any assistance.

MDI computer labs for helping me use the software and downloading the journals needed for my dissertations;

Management of the MDI faculty for tireless efforts to encourage students to professional development. Also to the staff of the Dean's Office for forwarding the correspondence sent on my behalf.

Finally, I would like to thank my organization WNS (Holdings) Limited, India and in particular Research & Analytics for providing me with this opportunity.




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automatic document feeder

Comprehensive Dickey-Fuller test

U.S. dollar

US dollar


Indian national rupee


Gross national product


Statistical analysis system


SAS correlation procedure


Regression procedure in SAS


GDP, nominal [bn. U.S. DOLLAR]


GDP, real (2005) [billion USD]


Inflation [%y/y]


Foreign reserves [USD billion]


Interest, long-term [ppa]


Interest, short term [ppa]


Trade balance, BOP [bn. U.S. DOLLAR]


Foreign direct investment, net, BOP [bn. U.S. DOLLAR]


Exports, services, BOP [bn. U.S. DOLLAR]


Exports, goods, BOP [bn. U.S. DOLLAR]


Interest, short-term, real [ppa]


Interest rate, long term, real [ppa]


Gross Domestic Product [$250,000,000]


GDP, nominal [bn. INR]


GDP, real (2005) [mn. INR]


Inflation [%y/y]


Foreign exchange reserves [billion. INR]


(Video) Imports, Exports, and Exchange Rates: Crash Course Economics #15

Interest, long-term [ppa]


Interest rate, short term [ppa] (CF)


Trade balance, BOP [billion INR]


Foreign direct investment, net, BOP [bn. INR]


Exports, services, BOP [bn. INR]


Exports, goods, BOP [bn. INR]


Interest, short-term, real [ppa]


INR to USD exchange rate, approximately [INR to USD]


LC to USD Exchange Rate, eop [INR to USD]


In today's truly globalized world, where international trade practices have developed to a greater extent, tracking the exchange rate plays a key role in realizing real profits. Think of a scenario where some exporting company has promised to provide goods/services at a certain time for a predetermined foreign currency amount, and somehow the foreign currency becomes cheaper during that certain time (currency devaluation) . In this scenario, the profits actually realized will therefore decrease and the exporter may also incur losses in some extreme cases (cases where margins are very low). It is a difficult and unpredictable situation when you are exposed to the risk of currency fluctuations and the economic scenario works against the company. Thus, this example clearly shows that the movement of the exchange rate is an important subject of study. Therefore, it is of great importance for different categories of institutions exposed to the risk of changes in exchange rates, e.g. Importers, exporters, international investors, etc. With most countries following an open economy these days, the ability to predict the tighter range of exchange rates has become really crucial.

We aim to address this kind of unpredictability in exchange rate scenarios to some extent so that institutions exposed to the risk of exchange rate fluctuations can make wise decisions in such situations. The aim of this study is to determine the macroeconomic indicators that can influence the exchange rate between two countries, and then to examine the degree of influence these variables can have on the exchange rate. Finally, develop a predictive model that can predict the future exchange rate based on the macroeconomic environment.

If the various institutions exposed to the risk of exchange rate fluctuations can predict the exchange rate in advance, they can make more efficient decisions. While on the one hand we focus on deriving a predictive model to predict currency rates as accurately as possible, on the other hand we also believe that short-term currency rates depend to a greater extent on microeconomic factors. Changes in the supply and demand of foreign currencies against the domestic currency and market sentiment continue to affect short-term exchange rates. However, the study of microeconomic factors is beyond the scope of these studies.

Problem statement: The aim of the study is to assist institutions exposed to currency risk in effective currency risk management. The focus will be on the exchange rate between the US currency, USD, and the Indian currency, INR.

We will study the quarterly movements of various macroeconomic factors from the point of view of the US and Indian economies and try to narrow down the list of key factors to develop a forecasting model.

Peer-reviewed literature: There is an enormous amount of theoretical and experimental research on the exchange rate. Predicting the exchange rate is a controversial topic among researchers. There are many studies on forecasting or forecasting the exchange rate that have been done in different dimensions. This easily shows that with shrinking trade borders and expanding foreign trade, this field of exchange rate forecasting still attracts many researchers and scientists from all over the world. Researchers have done a lot of work to uncover the hidden trend and estimate the behavior of the exchange rate. With the increase in international trade practices, various economists around the world are constantly trying to determine the determinants of currency fluctuations.

A study on the basic model

In 1995, Nelson C. Mark discovered that models are useful in forecasting exchange rates over the long term. After reviewing data for five major economies, Mark found that regressions of multi-period changes in the exchange rate log on the exchange rate log deviation provide solid evidence of long-term changes in the log of nominal exchange rates. According to the article, the noise generated by changes in the short horizon is averaged over time, so movements in the exchange rate can be determined by fundamental factors. In his research, he shows that coefficient estimates follow a pattern of nominal stiffnesses, albeit gradually, but that this causes the exchange rate to adjust to nominal or real shocks. For three of the four exchange rates he studied, out-of-sample projections outperformed the drift of a less random walk over a longer time horizon. He investigated the extent to which exchange rate deviations from the fundamental value are useful in forecasting long-term exchange rates. The empirical work was limited to one-variable regression analysis to easily characterize the predictive relationship.

Although his empirical work was very successful in finding empirical relativity between the exchange rate and fundamental factors, the research had some limitations because the relative time series were short, making the asymptotic reference unreliable.

Later work cast doubt on long-term forecasts of the exchange rate. There are certain schools of thought that believe in the predictive power of non-linear models. Models play a role in forecasting the exchange rate when they are far from base.

Models of the present value of the exchange rate

It was believed that many exchange rate models could be written to be explained as a weighted sum of current fundamentals such as money supply, prices, production levels, and the expected future value of the exchange rate, with little importance given to current fundamentals versus expectations. Engel and West challenged this standard criterion in 2004 and found that for this class of models, if the fundamentals of order 1 are integrated (that is, their first difference is stationary) and the discount factor is close to unity, the exchange rate will be approximately , he followed any step. According to their research, the exchange rate is determined by fundamental factors, but a floating exchange rate between countries with different inflation rates is well approximated as a random hike. They found evidence that the relationship between the exchange rate and fundamentals is consistent with exchange rate-based asset valuation models. First, they proved how a random hike in asset prices can result from a discount factor close to unity in a present-value model. They successfully applied this theorem to various exchange rate models and provided evidence that changes in the exchange rate help future fundamentals

M. B. Devereux and C. Engel studied "Expectations and Exchange Rate Policy" in 2006. The article deals with the implications of the fact that exchange rates mainly respond to news about future fundamentals. According to the new Keynesian economics, the goal should be to eliminate distortions due to sticky nominal prices. Ideally, monetary policy should aim to replicate the outcome that would be achieved if nominal prices were flexible. But the problem arises when, in an open economy, the nominal exchange rate of a few countries reacts to news about the future, as there are nominal commodity prices fixed in each country's currency. Then, along with a change in the nominal exchange rate, relative prices must change (prices of goods in one currency relative to prices in another currency). The problem is that these relative prices change over time as news emerges about future fundamentals that determine the nominal exchange rate. And if good prices were elastic, relative commodity prices would not be affected by the news of the future that determines the nominal exchange rate. Research argues for the fact that since most currency movements come from news of these future fundamentals; most exchange rate movements generate inefficient relative price movements. They argue that there is a case for monetary policy to address unexpected changes in nominal exchange rates in addition to the inflation target.

There have been many other studies and research papers, but there doesn't seem to be a unanimous consensus on how to predict the exchange rate.


In "Forecasting Exchange Rates in Transitional Economies: A Comparison of Multivariate Time Series Models," Cuaresma and Hlouskova compare the accuracy of forecasts with various multivariate models such as Unbounded VAR, BVAR, VEC, Bayesian VEC, and Deterministic Bounded VAR when applied to exchange rate forecasts various Central and Eastern European currencies against the Euro and the US Dollar. Several factors determining the exchange rate in such economies, called transition economies by Cuaresma and Hlouskova, have been studied. The results reinforce and confirm the conclusions of Meese and Rogoff (1983) and provide further evidence of the difficulties experienced by more sophisticated time series models (in this case VAR, VEC, BVAR, BVEC and limited VAR models with different specifications) in outperforming time series models naive random walk predictions of exchange rates. (res.)

In another article from the FLORIDA INTERNATIONAL UNIVERSITY Miami, Florida entitled "ESSAYS ON EXCHANGE RATE ECONOMICS", Yan Shu (2008) explored issues related to better understanding exchange rate behavior. It is clear from the extensive research available on this topic that exchange rate modeling and forecasting relies on fate variables whose behavior and exchange rate influence are difficult to determine. Decades ago, Meese and Rogoff (1983) empirically analyzed several major macrostructural models based on the monetary and wealth theory of exchange rate determination. They found that none of these models could outperform the naive random walk model in terms of out-of-sample prediction accuracy over a short time horizon. Several researchers published this, backing up the multi-currency findings.

There is a lot of literature available on time series techniques for currency movements. Many researchers have dabbled in nonlinear modeling of exchange rates, but with little success. (answer)

Research problem:

Having studied the limitations of modeling exchange rate behavior by many researchers and scholars in the past, and several efforts still in progress, this research paper attempts to investigate and deduce the following:

Exchange rate change USD/INR

Factors Affecting USD/INR Movements

An econometric model to forecast the USD/INR exchange rate

Challenges and problems in the development of this model and opportunities for further refinement and fine-tuning

assumed assumptions:

The economic conditions of the United States and India are solely responsible for shaping the USD/INR exchange rate, and no other country's economy influences this exchange rate combination over the long term

The Indian rupee and the US dollar are fully liquid currencies and neither country makes any explicit attempt to influence exchange rates

Research project:

Methodology adopted for the study

Several economic indicators were tested to measure their impact on the USD/INR exchange rate in both the US and Indian scenarios, and the following variables were ultimately narrowed down for further investigation


GDP, nominal [bn. U.S. DOLLAR]

GDP, real (2005) [billion USD]

Inflation [%y/y]

Foreign reserves [USD billion]

Interest, long-term [ppa]

Interest, short term [ppa]

Trade balance, BOP [bn. U.S. DOLLAR]

Foreign direct investment, net, BOP [bn. U.S. DOLLAR]

Exports, services, BOP [bn. U.S. DOLLAR]

Exports, goods, BOP [bn. U.S. DOLLAR]

Interest, short-term, real [ppa]

Interest rate, long term, real [ppa]

Gross Domestic Product [$250,000,000]

Unemployment Rate, US

Brent oil spot price

Spot gold price in USD


GDP, nominal [mln. LC]

BBP, reëel (2005) [mld. LC]

Inflation [%y/y]

Foreign exchange reserves [billion. LC]

Interest, long-term [ppa]

Interest, short term [ppa]

Handelsbalans, BOP [mld. LC]

Foreign direct investment, net, BOP [bn. LC]

Exports, services, BOP [bn. LC]

Exports, goods, BOP [bn. LC]

Interest, short-term, real [ppa]

Exchange rate

LC to USD exchange rate, average, period average

Exchange rate LC to USD, end of period

Various types of statistical techniques were used to investigate the relationship between these variables, then econometric modeling was used to derive a causal relationship between various economic factors (independent variables) and the USD/INR exchange rate (dependent variable) .

Example data and data source:

Data for all required variables are not changed/published at a very high frequency, e.g. daily or monthly, so data for all variables is only collected on a quarterly basis

Data was collected from Q1 1990 to Q2 2012.

Below is a snapshot of the data tables

Sample data India (Table 1)










GDP, nominal [bn. INR]









GDP, real (2005) [mn. INR]









(Video) Floating and Fixed Exchange Rates- Macroeconomics

Inflation [%y/y]






10:35 am



Foreign exchange reserves [billion. INR]









Interest, long-term [ppa]








12:25 p.m

Interest rate, short term [ppa] (CF)

2:75 p.m

2:25 pm

1:50 pm


14.00 hours




Trade balance, BOP [billion INR]









Foreign direct investment, net, BOP [bn. INR]









Exports, services, BOP [bn. INR]









Exports, goods, BOP [bn. INR]









Interest, short-term, real [ppa]









INR to USD exchange rate, approximately [INR to USD]









LC to USD Exchange Rate, eop [INR to USD]




(Video) Intl Economics - Chapter 12: Exchange Rate Determination






US Sample Data (Table 2)

United States









GDP, nominal [bn. U.S. DOLLAR]









GDP, real (2005) [billion USD]









Inflation [%y/y]









Foreign reserves [USD billion]

10:45 p.m








Interest, long-term [ppa]









Interest, short term [ppa]









Trade balance, BOP [bn. U.S. DOLLAR]









Foreign direct investment, net, BOP [bn. U.S. DOLLAR]









Exports, services, BOP [bn. U.S. DOLLAR]









Exports, goods, BOP [bn. U.S. DOLLAR]






(Video) Income and Wealth Inequality: Crash Course Economics #17




Interest, short-term, real [ppa]









Interest rate, long term, real [ppa]









Gross Domestic Product [$250,000,000]









Price of Brent crude oil in dollars per barrel









USD gold price









Unemployment rate at the end of the quarter









Data sources: Various Indian, US and international data and statistical sources were referenced to obtain the required data for all variables listed above. Below is a detailed list of sources from which online data has been collected:

IHS global insight

International Monetary Fund (IMF)

International Financial Statistics (IFS)

Reserve Bank of India

Central Statistical Organization

Office of Economic Analysis

World Gold Council (

Bureau of Labor Statistics (

United States Energy Information Administration (

Data analysis

Selection of the period to study the movement of the exchange rate.

For all the economic indicators mentioned above. But all the use of the data was not possible during model creation. Here the purpose is to derive a model to predict the exchange rate, and it cannot be modeled over a period where the USD/INR exchange rate was fixed or pegged. Modeling can only be performed in the period when the USD/INR exchange rate actually started to move.

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USD/INR exchange rate before 1991 - In 1991, India still had a fixed exchange rate system where the rupee was pegged to the value of a basket of currencies from major trading partners. India started to experience balance of payments problems from 1985 and by the end of the 1990s it was in serious economic trouble. The government was on the brink of default and its foreign exchange reserves had dried up to such an extent that India could barely finance three weeks' worth of imports. (res.)

USD/INR exchange rate after 1991 - Prior to the 1990s, there was a period of severe economic crisis for India and in 1991, the Indian government enacted several reforms that led to the liberalization of the Indian economy and thus opened the door for foreign investment.

The initiation of economic reforms resulted, among other things, in a downward adjustment of the exchange rate in two steps of 9 percent and 11 percent between July 1 and July 3, 1991, to counter the massive depletion of foreign exchange reserves, restore investor confidence, and improving domestic competitiveness. The Liberalized Exchange Rate Management System (LERMS) was introduced in March 1992 and included a dual exchange rate regime for a transitional period. In March 1993, the dual exchange rate system was replaced by the single exchange rate system. The experience of the market-determined exchange rate system in India since 1993 has generally been described as "satisfactory" as the Indian market was in order for most of that period. Volatility episodes were effectively managed with timely monetary and administrative measures. (Res.). After 1993, the rupee actually started to rise.

This forms the basis of the time window that we will focus on in our USD/INR exchange rate analysis, and we have extracted USD/INR data points and drivers for this time frame.

Selection of Determining Variables - US and India Economic Indicators

We have carefully selected a few of the various current macroeconomic indicators and will explain one by one why these variables were chosen

1. Economic Growth (GDP, GNP): The growth of a country's economy, which is reflected in GDP/GNP values, indicates the strength of the economy. An increase in GDP can mean a greater demand for the domestic currency or an increase in the supply of foreign currency into the economy as an investment.

2. Inflation: Rising inflation indicates a lower purchasing power of the national currency compared to other currencies, and thus a lower exchange rate. It has been observed that countries with high inflation tend to depreciate their currencies relative to developed economies with lower inflation rates

3. Interest Rates: Interest rates play an important role in determining exchange rates. Higher interest rates would mean more foreign investment, which would push up the currency

4. Current Account Balance: A current account deficit means that a country has a negative trade balance and has to pay more in foreign currency. Therefore, the domestic country would borrow more in foreign currency to pay off its debts. Excessive demand for foreign currency lowers the exchange rate

5. Exports: More exports would mean a greater real appreciation of domestic currency demand

6. Foreign Direct Investment: In today's global economy, FDI is a major factor influencing exchange rates. If the domestic country attracts more foreign currency through foreign direct investment, it would mean an appreciation of the domestic currency and relative to the domestic currency.

Trend analysis factor and exchange rate movement

Movement of selected macroeconomic factors (Indian and American) in the period of w.r.t. changes in the USD/INR exchange rate

It is clear that in 2008-2009 when the GDP (nominal) of US fell and GDP (nominal) of India rose sharply, the fall in the exchange rate became apparent when the value of USD 1 fell from Rs 50 to Rs 45 .

US inflation data clearly shows a negative correlation between inflation rates and USD/INR rates.

The foreign reserve numbers by themselves show no effect on past exchange rate data for both the Indian and US markets, but this would become clearer when we model the data to control for a causal effect.

US long-term interest rates are clearly showing some impact on the value of the USD against the Indian rupee

Short-term interest rates do not appear to play a major role in determining long-term movements in the exchange rate.

Trade balance data for both the US and India clearly show some impact on exchange rates, with the relative gains of the US trade balance showing a strong USD against the rupee and the like

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What is econometric models of forecasting exchange rates? ›

Econometric Models

It is a method that is used to forecast exchange rates by gathering all relevant factors that may affect a certain currency. It connects all these factors to forecast the exchange rate. The factors are normally from economic theory, but any variable can be added to it if required.

What is the exchange rate US dollar to Indian rupee forecast? ›

Experts expect the rupee to trade in the range of 80-89 per dollar. The current USD/INR exchange rate is 81.52.

How would an economist will define the exchange rate between two currencies? ›

An exchange rate between two currencies is defined as the rate at which one currency will be exchanged for another. The real exchange rate is the purchasing power of a currency relative to another at current exchange rates and prices.

How exchange rate is determined in economics? ›

In a floating regime, exchange rates are generally determined by the market forces of supply and demand for foreign exchange. For many years, floating exchange rates have been the regime used by the world's major currencies – that is, the US dollar, the euro area's euro, the Japanese yen and the UK pound sterling.

What is the best model to predict exchange rate? ›

Purchasing power parity looks at the prices of goods in different countries and is one of the more widely used methods for forecasting exchange rates due to its indoctrination in textbooks. The relative economic strength approach compares levels of economic growth across countries to forecast exchange rates.

How do you write an econometric model? ›

To make an econometric model to assess the relationship between two or more variables, a series of steps need to be followed.
  1. Step 1: Make the hypothesis. ...
  2. Step 2: Collect the data. ...
  3. Step 3: Identify the nature of data. ...
  4. Step 4: Identify the econometric method. ...
  5. Step 5: Write the mathematical equation(s)
Feb 28, 2022

Why USD is getting stronger compared to INR? ›

The answer is to control inflation. As interest goes high. The interest rate of saving accounts, FD also increased, credit cards, home loan interest goes high, people invest more than spending, circulation of the money goes down in the market, and demand goes down as a result price comes down.

Why US dollar rate is high in India? ›

India imports commodities from the US instead of exporting on its own which is why the value of the Dollar is high due to the number of exports.

What is the exchange rate of India rupee to a US dollar? ›

0.01218 USD

What is the relationship between exchange rate and economy? ›

The exchange rate affects the real economy most directly through changes in the demand for exports and imports. A real depreciation of the domestic currency makes exports more competitive abroad and imports less competitive domestically, thereby increasing demand for domestically produced goods.

What are the methods of exchange rate determination? ›

They are: Multiplier method. Divisor method. Triangulation and No inverse method.

When an economist says that a currency has become stronger they mean that? ›

The dollar is considered strong when it rises in value against other currencies in the foreign exchange market. A strengthening U.S. dollar means it can buy more of a foreign currency than before.

What are the factors that affect exchange rate in an economy? ›

Exchange rates are determined by factors, such as interest rates, confidence, the current account on balance of payments, economic growth and relative inflation rates.

What factors determine currency exchanges? ›

7 key factors that influence foreign exchange rates
  • Interest and inflation rates. Inflation is the rate at which the cost of goods and services rises over time. ...
  • Current account deficits. ...
  • Government debt. ...
  • Terms of trade. ...
  • Economic performance. ...
  • Recession. ...
  • Speculation.
Sep 6, 2022

What are three of the main approaches to exchange rate forecasting? ›

The medium-term predictability of exchange rate movements is examined using three models of fundamentals: purchasing power parity, the monetary model, and uncovered interest parity.

What are the two main methods of forecasting exchange rates? ›

Based on the information set used by the forecaster, there are two pure approaches to forecasting foreign exchange rates: (1) The fundamental approach. (2) The technical approach. The fundamental approach is based on a wide range of data regarded as fundamental economic variables that determine exchange rates.

What are the three models of exchange rate? ›

In the following, we explain three models of exchange rate determination, namely, the purchasing power parity(PPP), the monetary model and the portfolio balance theory.

What is econometric models summary? ›

Econometric models are statistical models used in econometrics. An econometric model specifies the statistical relationship that is believed to hold between the various economic quantities pertaining to a particular economic phenomenon.

What are the 2 econometric models? ›

There are two broad classes of economic models—theoretical and empirical.

What is an example of economic model and econometric model? ›

Y=B1+B2X, Keynesian consumption function is an example of an economic model. This relation is deterministic. Y=B1+B2X+ U. This stochastic relation is an example of the econometric model.

Why does INR decrease with USD? ›

Current account deficit

The rising current account deficit has depleted our foreign exchange reserve and thus led to a fall in the value of the Indian Rupee.

What happens if dollar value increases in India? ›

Changes in fuel prices

Fuel and oil commodities are traded in Dollars. India is the largest importer of crude oil, and any change in the Dollar index affects crude oil prices and thus the Indian economy. If the Dollar index rises, crude oil and other commodities become costlier.

How does the US dollar become stronger? ›

In addition to capital inflows due to high interest rates, the dollar has also benefitted from strong foreign direct investment in recent years. Direct investment includes ownership in companies or real estate.

What is the strongest currency in the world? ›

The highest currency in the world is none other than Kuwaiti Dinar or KWD. Initially, one Kuwaiti dinar was worth one pound sterling when the Kuwaiti dinar was introduced in 1960. The currency code for Dinars is KWD. The most popular Kuwait Dinar exchange rate is the INR to KWD rate.

What happens if dollar value decreases in India? ›

All this leads to inflation, and a depletion of our forex reserves because we're sending out more dollars on crude oil. This reduces our ability to import other goods that we need.

What is the highest USD rate in India ever? ›

Highest: 83.002 INR on 19 Oct 2022. Average: 82.153 INR over this period.

What are the five main effects of the exchange rate on an economy? ›

Key Takeaways. Currency exchange rates can impact merchandise trade, economic growth, capital flows, inflation and interest rates.

What are the benefits of exchange rate on the economy? ›

A fixed exchange rate helps to ensure the smooth flow of money from one country to another. It helps smaller and less developed countries to attract foreign investment. It also helps the smaller countries to avoid devaluation of their currency and keep inflation stable.

What are the advantages of exchange rate in economics? ›

The advantages of a fixed exchange rate include:

Providing greater certainty for importers and exporters, therefore encouraging more international trade and investment. Helping the government maintain low inflation, which can have positive long-term effects such as keeping down interest rates.

What is the conclusion of exchange rate determination? ›

Conclusion. Exchange rate determination is a very important part of macroeconomics. As the currency is the moving force of an economy, changes in its rates affect everyone. Therefore, governments try to increase the value of their currencies so that the balance of payments could be managed at a satisfactory level.

Is it better for an economy to have a strong or weak currency? ›

The implications of words such as "strong" and "weak" can mislead people to believe that an appreciating currency is always better for the economy than a depreciating currency, but this is not the case. In fact, there is no simple connection between the strength of a country's currency and the strength of its economy.

Why does a strong dollar hurt the economy? ›

The strong dollar feeds into inflation pressures abroad.

When a country's currency weakens against the dollar, the price of imports from the United States rises, putting pressure on prices. On average, the pass-through of a 10 percent dollar appreciation into inflation abroad is 1 percent.

What will happen if the U.S. dollar is no longer the world currency? ›

No matter the world reserve currency, you'll still owe your mortgage, credit card, car, and college tuition. The big difference is that those dollars will now be worth mere pennies. It will be two, three, or even ten times as hard to pay for anything, including food, water, shelter, etc.

What is the biggest factor in determining exchange rates? ›

10 Factors that influence currency exchange rates:
  • Inflation >
  • Interest rates >
  • Government Debt/Public >
  • Political Stability >
  • Economic Recession >
  • Terms of Trade >
  • Current account deficit >
  • Confidence and speculation >
Feb 16, 2023

When might it be important to know a currency's exchange rate? ›

An exchange rate is the rate at which one currency can be exchanged for another between nations or economic zones. It is used to determine the value of various currencies in relation to each other and is important in determining trade and capital flow dynamics.

What is the relationship between inflation and exchange rates? ›

How Does Inflation Affect Currency Conversion Rates? When inflation is higher, this tends to have a depressing affect on the value of a country's currency. This is because increased inflation reduces the currency's buying power, which weakens it against other currencies.

What are 3 factors that determine exchange rates in the long run? ›

In addition, three other factors affect exchange rates in the long run: relative trade barriers, differential preferences for domestic and foreign goods, and differences in productivity.

What are the 4 types of exchange rate system? ›

There are four main types of exchange rate regimes: freely floating, fixed, pegged (also known as adjustable peg, crawling peg, basket peg, or target zone or bands ), and managed float.

What are the variables of exchange rate? ›

Four main factors have been identified to measure the effect on exchange rate, i.e. broad money supply (M2), lending rate, inflation and real GDP.

What are the econometric models? ›

Some of the common econometric models are:
  • Linear regression.
  • Generalized linear models.
  • Probit.
  • Logit.
  • Tobit.
  • ARIMA.
  • Vector Autoregression.
  • Cointegration.

What is the econometric forecasting technique? ›


This quantitative type of forecasting combines sales data with information on outside forces that affect demand. Then you create a mathematical formula to predict future customer demand. The econometric demand forecasting method accounts for relationships between economic factors.

What are the different econometric forecasting models? ›

There are three approaches to estimating and forecasting such models; (1) Linear Probability model (LPM), (2) Logit model, (3) Probit model and Tobit model.

What is the economic model forecasting? ›

Economic forecasting involves the building of statistical models with inputs of several key variables, or indicators, typically in an attempt to come up with a future gross domestic product (GDP) growth rate.

What are 3 different types of economic models that are used in economics? ›

The most commonly used economic models can be given as visual economic models, mathematical economic models, and economic simulations.

How econometrics can be used as a tool for forecasting and prediction? ›

In the simplest terms, econometricians measure past relationships among such variables as consumer spending, household income, tax rates, interest rates, employment, and the like, and then try to forecast how changes in some variables will affect the future course of others.

What are economic and econometric models explain in detail? ›

An economic model is a set of assumptions that describes the behaviour of an economy, or more generally, a phenomenon. An econometric model consists of - a set of equations describing the behaviour. These equations are derived from the economic model and have two parts – observed variables and disturbances.

What are the advantages of econometric models? ›

First, econometric modeling—it reduces the bias in measurement. That's its first advantage. Second, it correctly or accurately isolates out the impact of the media (the impact of media on sales) from the impact of all of the other factors that influence sales.

What are the three methods that may be used for economic forecasting? ›

- [Instructor] There are three methods of forecasting that are commonly used in economics and business analytics, causal methods, time series methods, and qualitative methods. Each of these three different methods has various tools and techniques that fall underneath the silo in question.

What are the four types of models used in economic analysis? ›

There are four types of models used in economic analysis, visual models, mathematical models, empirical models, and simulation models.

What is economic forecasting summary? ›

Economic forecasting makes use of historical data points that have been released in previous economic reports for countries or geographical regions. Generally, economic forecasting is centered around predicting the growth in Gross Domestic Product (GDP) for an economy.


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