A MACROECONOMIC PERSPECTIVE OF AFTA'S PROBLEMS AND PROSPECTS

The Association of Southeast Asian Nations (ASEAN) and the impressive economic performance of most of its members have increased the weight of the region's views in world fora. However, ASEAN has been unsuccessful in fostering a regional integration arrangement (RIA) leading to an increase in intraregional trade and foreign direct investment. In January 1992, ASEAN launched the Asean Free Trade Area (AFTA) seeking to establish a free trade area (FTA) by 2008.
Market integration increases economic interdependence and thereby raises the need for policy integration and discipline. This paper argues that a number of difficulties that ASEAN faced in promoting intraregional trade are likely to continue to affect AFTA (e.g., low economic complementarity and macroeconomic imbalances requiring large changes in equilibrium real exchange rates). The experience of other RIAs suggests other potential problems.
AFTA's prospects of evolving into deeper forms of sustainable integration are remote. Some cooperation in areas of common interest seems likely.     

Community Health Purchasing Alliances (CHPAs): how Florida CHPAs are affecting employers. A case study

Florida's health insurance reforms for small employers can be viewed as two distinct initiatives: insurance reform and the community health purchasing alliances (CHPAs). While small employer insurance reform legislation appears to have expanded access to coverage, the administrative structure of the CHPA still has a long way to go to capture the confidence of the marketplace.     

Bayesian and Frequentist Inference for Ecological Inference: The R×C Case

In this paper we propose Bayesian and frequentist approaches to ecological inference, based on R × C contingency tables, including a covariate. The proposed Bayesian model extends the binomial-beta hierarchical model developed by K ing , R osen and T anner (1999) from the 2×2 case to the R × C case. As in the 2×2 case, the inferential procedure employs Markov chain Monte Carlo (MCMC) methods. As such, the resulting MCMC analysis is rich but computationally intensive. The frequentist approach, based on first moments rather than on the entire likelihood, provides quick inference via nonlinear least-squares, while retaining good frequentist properties. The two approaches are illustrated with simulated data, as well as with real data on voting patterns in Weimar Germany. In the final section of the paper we provide an overview of a range of alternative inferential approaches which trade-off computational intensity for statistical efficiency.     

Semiparametric Estimation of a Duration Model

Within the framework of the proportional hazard model proposed in Cox (1972), Han and Hausman (1990) consider the logarithm of the integrated baseline hazard function as constant in each time period. We, however, proposed an alternative semiparametric estimator of the parameters of the covariate part. The estimator is considered as semiparametric since no prespecified functional form for the error terms (or certain convolution) is needed. This estimator, proposed in Lewbel (2000) in another context, shows at least four advantages. The distribution of the latent variable error is unknown and may be related to the regressors. It takes into account censored observations, it allows for heterogeneity of unknown form and it is quite easy to implement since the estimator does not require numerical searches. Using the Spanish Labour Force Survey, we compare empirically the results of estimating several alternative models, basically on the estimator proposed in Han and Hausman (1990) and our semiparametric estimator.     

Sectoral Shocks and Metropolitan Employment Growth

In this paper, we study the sources of industry employment growth in each of five metropolitan statistical areas (MSAs). The objective is to understand the relative importance of aggregate disturbances versus local sectoral shocks in generating observed employment fluctuations at the MSA level. The empirical evidence presented in this paper derives from structural vector autoregressions (SVARs), estimated for each of the five MSAs. Estimations use monthly employment data covering nine one-digit industrial categories for the period 1951:1–1999:8, as well as two variables that capture the influences of aggregate (i.e., national) shocks on MSAs. We find that within-MSA industry shocks explain considerably more of the forecast error variance in industry employment growth than do aggregate shocks. Sectoral shocks account for between 87 and 94% of the 36-month-ahead forecast error variance. Among individual local sectors, shocks to MSA-specific government, manufacturing, and service sector employment growth are the predominate sources of variability.     

Multivariate stable ARMA processes with time dependent coefficients

This paper considers the class of m-variate autoregressive moving average (ARMA) processes with stable innovations and time dependent coefficients. A set of suitable AR and MA regularity conditions is given to ensure existence and uniqueness of valid solutions. A simple form of the above solution is expressed in terms of one sided Green's matrix functions associated with the AR operator. We solve the prediction problem arising in this class of models. A few examples are added to support the general theory.     

The Rights of Employees with Disabilities: Supreme Court Interpretations of the Americans with Disabilities Act and Their Implications for Human Resource Management

The Americans With Disabilites Act (ADA) of 1990 provides broad protection to an estimated 43 million Americans against discrimination in many facets of their lives. Title I of the Act prohibits discrimination in employment. Title III of the Act, which prohibits discrimination in public accommodation, has also impacted the employment relationship. Eight years after the passage of the Act, the U.S. Supreme Court issued its first ruling under the ADA. Two subsequent decisions have been rendered that further interpret the statute and the Court has repeatedly denied to review cases that deal with another key interpretation of the ADA. This paper analyzes these cases and decisions and their implications for management practices.     

Lower Bound Restrictions on Intensities in Data Envelopment Analysis

We propose an extension to the basic DEA models that guarantees that if an intensity is positive then it must be at least as large as a pre-defined lower bound. This requirement adds an integer programming constraint known within Operations Research as a Fixed-Charge (FC) type of constraint. Accordingly, we term the new model DEA_FC. The proposed model lies between the DEA models that allow units to be scaled arbitrarily low, and the Free Disposal Hull model that allows no scaling. We analyze 18 datasets from the literature to demonstrate that sufficiently low intensities—those for which the scaled Decision-Making Unit (DMU) has inputs and outputs that lie below the minimum values observed—are pervasive, and that the new model ensures fairer comparisons without sacrificing the required discriminating power. We explain why the low-intensity phenomenon exists. In sharp contrast to standard DEA models we demonstrate via examples that an inefficient DMU may play a pivotal role in determining the technology. We also propose a goal programming model that determines how deviations from the lower bounds affect efficiency, which we term the trade-off between the deviation gap and the efficiency gap.     

Tests based on φ-divergences for bivariate symmetry

In this paper we introduce a family of test statistics for testing symmetry based on φ-divergence families. These test statistics yield the likelihood ratio test and the Pearson test statistic as special cases. Asymptotic distribution for the new test statistics are derived under both the null and the alternative hypotheses. A simulation study is presented to see that some new test statistics offer an attractive alternative to the classical Pearson test statistic for the problem of symmetry. Received: May 2000