Agricultural and Food Policy, Research Methods/Statistical Methods

[If two linear models have different sets of explanatory variables and the same variable to be explained, the residual variance of the correct model (S extasciicircum2"n) has a smaller mean value than that of the incorrect one (t extasciicircum2"n). This note shows under fairly general conditions that S extasciicircum2"n extless t extasciicircum2"n will hold with probability arbitrarily close to 1 provided that the sample size n is large enough.]

Agricultural and Food Policy, Research Methods/Statistical Methods

IN RECENT YEARS a number of theoretical and statistical investigations' in the field of business-cycle analysis have made use of differeince equations, or mixed difference and differential equations. These equations serve to study the possible endogenous movements of a schematized economic system governed by a set of as many structural relations as there are variables, the movements of which are considered. In the investigations referred to, the treatment of such a set of equations has been to eliminate successively all variables but one, which leaves one from which the possible movements of the system under consideration are studied. If the final equation in the variable Zt is a linear homogeneous difference equation or mixed difference and differential equation, possible movements of Zt are found by substituting for it in the final equation an expression of the form2

The 2009 CARD Act limited credit card lenders' ability to raise borrowers' interest rates on the basis of new information. Pricing became less responsive to public and private signals of borrowers' risk and demand characteristics, and price dispersion fell by one‐third. I estimate the efficiency and distributional effects of this shift toward more pooled pricing. Prices fell for high‐risk and price‐inelastic consumers, but prices rose elsewhere in the market and newly exceeded willingness to pay for over 30% of the safest subprime borrowers. On net, average traded prices fell and consumer surplus rose at all credit scores. Higher consumer surplus was partly driven by a fall in lender profits, and partly by the Act's insurance value to borrowers who could retain favorable pricing after adverse changes to their default risk. The relatively high level of pre‐CARD‐Act markups was crucial for realizing these surplus gains.