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A Case Study in Prediction: The Market for Watermelons
This paper discusses two forecasting experiments involving models of the watermelon market. The first experiment compares the forecasts of an interdependent model estimated by limited information, single equation with those of a model using least squares reduced form. The second experiment compares the forecasts of the interdependent model with those of a causal chain model. It is found that the forecasts of the interdependent model are generally better than those of the alternative models.
Talks on Planning
Measurement in Economics. Studies in Mathematical Economics and Econometrics in Memory of Yehuda Grunfeld
A Model of Economic Growth in Rostovian Stages
This paper gives a non-linear growth model, which explains the development of an economy through stages somewhat similar to the Rostovian stages. Non-linearity is introduced by including the inaugmentable factor of land or natural resources in the production function along with labor and capital, and by recognising that net saving is not a linear homogeneous function of income alone, but might be affected by the distribution of income and the interest rate and tends to be negative when per capita income is very low. Furthermore, population growth is assumed to follow a NeoMalthusian pattern. The effects of non-neutral as well as neutral technical progress are discussed in this paper.
Essays on the Structure of Social Science Models
On the Economic Welfare Function
This welfare index defines the preference ordering of the society among all possible social states. In this case, a social state is expressed as a point in an m x n-dimensional vector x -(x, . .., x'), and the welfare index can be considered as a utility index defined in an m x n-dimensional space. We can therefore define the marginal rate of substitution for society between the mth individual's nth commodity and the ith individual's jth commodity. Set W= C (constant) and consider this relation as the function that determines the value of x' depending on the values of other x7.s. Differentiate this relation with respect to X4. Then, we get
Spurious Correlation Due to Deflating Variables
Abstract : This Memorandum shows that when a homogeneous linear regression of a normally distributed variable Y on two nromally distributed variables X and Z is deflated by Z, then when X and Y are uncorrelated the deflated dependent variable Y/Z and independent variable X/Z are either uncorrelated or perfectly correlated. Thus, existing approximations to the covariance of these deflated variables are poor. A new approximation to this covariance is given which has the same defect for normally distributed variables, but which could otherwise be better than existing ones. (Author)