This paper is connected with the empirical problems involved in the theoretical exchange rate models. Since the adoption of flexible exchange rate systems, a number of theoretical models of exchange rate determination have come into existence, which tried to explain the exchange rate behavior under different exchange rate systems. A review of empirical evidence on these models suggest that there are some empirical problems like poor fit, statistically insignificant parameters, sign reversals, serial correlation in the residuals, simultaneity and multicollinearity involved in these models. There is a need for a model, which is free from all these empirical problems. In the present paper, a simultaneous equation model has been developed, which has been tested for all these empirical problems. The variables used in the model are exchange rate of Indian rupee against US Dollar, Trade Balance, External Debt, Current Account Balance, Gross Domestic Product at current market prices and Money Supply. The causal chain of the proposed model runs from ER_t+1 Ù TR_t Ù ER_t-1 and ER_t Ù ED_t Ù M_t , where

ER_t+1 is the exchange rate at period t+1

ER_t-1 is the exchange rate at period t-1

TR_t is the trade balance of period t

ED_t is the external debt at period t

M_t is the money supply at period t

From this causal chain it is clear that the model is a recursive model. So recursive method in simultaneous equation models has been used to develop the model. Hence, each equation in the model has been estimated by using ordinary least squares estimates. To remove the serial correlation in the residuals, Praise-Winsten generalized least squares method is used. All the equations are tested for the empirical problems discussed above and it is found that the proposed model is free from all these empirical problems. The model is tested for the out-of-sample forecasting performance by using the data for the years 1999 and 2000. The results are compared with that of the random walk model. It is found that the proposed model outperforms the random walk model. The model can be used by business concerns