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In the LM model of interest rate determination, [1]: pp. 261–7 the supply of and demand for money determine the interest rate contingent on the level of the money supply, so the money supply is an exogenous variable and the interest rate is an endogenous variable.
Of course, changes in these variables in the opposite direction shift the IS curve in the opposite direction. The IS–LM model also allows for the role of monetary policy. If the money supply is increased, that shifts the LM curve downward or to the right, lowering interest rates and raising equilibrium national income.
This model uses the following variables: Y is real GDP; C is real consumption; I is real physical investment, including intended inventory investment; G is real government spending (an exogenous variable) M is the exogenous nominal money supply; P is the exogenous price level; i is the nominal interest rate; L is liquidity preference (real ...
The exogenous latent variables are background variables postulated as causing one or more of the endogenous variables and are modeled like the predictor variables in regression-style equations. Causal connections among the exogenous variables are not explicitly modeled but are usually acknowledged by modeling the exogenous variables as freely ...
According to whether all the model variables are deterministic, economic models can be classified as stochastic or non-stochastic models; according to whether all the variables are quantitative, economic models are classified as discrete or continuous choice model; according to the model's intended purpose/function, it can be classified as quantitative or qualitative; according to the model's ...
The IS curve joins all the pairs (Y,r) which satisfy the IS equation I(r)=S(Y) and the LM curve joins the pairs which satisfy the LM equation L(Y,r)=M. The point of intersection of the two curves tells us the income Ŷ and the rate of interest r̂. Under Keynes's Chapter 13 liquidity preference doctrine the LM curve will be
In the first stage, each explanatory variable that is an endogenous covariate in the equation of interest is regressed on all of the exogenous variables in the model, including both exogenous covariates in the equation of interest and the excluded instruments. The predicted values from these regressions are obtained:
may be seen as a matrix of row-vectors or of n-dimensional column-vectors, which are known as regressors, exogenous variables, explanatory variables, covariates, input variables, predictor variables, or independent variables (not to be confused with the concept of independent random variables).