Labor in the Puerto Rican Economy: Postwar Development and Stagnation

By Carlos E. Santiago | Go to book overview

NOTES
1.
Many studies appearing prior to the initiation of the island's industrialization program cited the constraints on Puerto Rico's economic development brought about by rapid population growth. Worth mentioning are those of Clark, et al. ( 1930) and Zimmerman ( 1940). At the start of industrial expansion, Perloff ( 1950) concluded that " Puerto Rico cannot hope to achieve higher levels of living or, possibly, even to maintain its present level of living over a long period of time without an integrated program aimed at checking the very rapid rate of population growth." This pessimistic appraisal, oftentimes overly pessimistic, is found over the years in both private and public documents. Also see Comité Interagencial de la Estrategi + ̂a de Puerto Rico ( 1975).
2.
Population estimates are compiled by the Puerto Rico Planning Board and updated continually with decennial census information of the U.S. Bureau of the Census. See Puerto Rico Planning Board ( 1979).
3.
The Korean case is an exception but can be explained by the conflict of the early 1950s.
4.
The Akaike Information Criterion (AIC) provides an efficient method of choosing one of many competing models. Let us express the competing models . The AIC is defined by a loss function based on the difference between the true and estimated distribution of a fitted model. The error is expressed as a function of the likelihood ratio of two probability distributions and measured by Kullback and Leibler's mean information for discrimination. The loss function proposed by Akaike is

(1.10)

where it is treated as a constant in the integration, Θ is a vector of parameters, and T is the number of observations. The Akaike Information Criterion is the predictor of W and can be expressed as

(1.11)

where p is the dimension of vector α. The objective is to find the specification that minimizes the AIC. See Amemiya ( 1985) for a discussion of the use of the Akaike Information Criterion.

5.
In contrast to the classical multivariate regression approach, the error structure in the ARMA model, et, is not assumed to be normally distributed with Et] = 0, Vart] = σ2 for all t, and Et, εt-j] = 0

-31-

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