A simple permutation test for clusteredness

Hierarchical clustering is a popular method for finding structure in multivariate data,resulting in a binary tree constructed on the particular objects of the study, usually samplingunits. The user faces the decision where to cut the binary tree in order to determine the numberof clusters to interpret and there are various ad hoc rules for arriving at a decision. A simplepermutation test is presented that diagnoses whether non-random levels of clustering are presentin the set of objects and, if so, indicates the specific level at which the tree can be cut. The test isvalidated against random matrices to verify the type I error probability and a power study isperformed on data sets with known clusteredness to study the type II error.

Pre-play communication and credibility: A test of Aumann's conjecture

The effectiveness of pre-play communication in achieving efficientoutcomes has long been a subject of controversy. In some environments,cheap talk may help to achieve coordination. However, Aumannconjectures that, in a variant of the Stag Hunt game, a signal forefficient play is not self-enforcing and concludes that an "agreementto play [the efficient outcome] conveys no information about what theplayers will do." Harsanyi and Selten (1988) cite this example as anillustration of risk-dominance vs. payoff-dominance. Farrell and Rabin(1996) agree with the logic, but suspect that cheap talk willnonetheless achieve efficiency. The conjecture is tested with one-waycommunication. When the sender first chooses a signal and then anaction, there is impressive coordination: a 94% probability for thepotentially efficient (but risky) play, given a signal for efficientplay. Without communication, efforts to achieve efficiency wereunsuccessful, as the proportion of B moves is only 35%. I also test ahypothesis that the order of the action and the signal affects theresults, finding that the decision order is indeed important. WhileAumann s conjecture is behaviorally disconfirmed when the signal isdetermined initially, the signal s credibility seems to be much moresuspect when the sender is known to have first chosen an action, andthe results are not statistically distinguishable from those whenthere is no signal. Some applications and issues in communication andcoordination are discussed.

Motivation, test scores and economic success

This paper argues that low-stakes test scores, available in surveys, may be partially determinedby test-taking motivation, which is associated with personality traits but not with cognitiveability. Therefore, such test score distributions may not be informative regarding cognitiveability distributions. Moreover, correlations, found in survey data, between high test scoresand economic success may be partially caused by favorable personality traits. To demonstratethese points, I use the coding speed test that was administered without incentives to NationalLongitudinal Survey of Youth 1979 (NLSY) participants. I suggest that due to its simplicityits scores may especially depend on individuals' test-taking motivation. I show that controllingfor conventional measures of cognitive skills, the coding speed scores are correlated with futureearnings of male NLSY participants. Moreover, the coding speed scores of highly motivated,though less educated, population (potential enlists to the armed forces) are higher than NLSYparticipants' scores. I then use controlled experiments to show that when no performance-basedincentives are provided, participants' characteristics, but not their cognitive skills, affect effortinvested in the coding speed test. Thus, participants with the same ability (measured by theirscores on an incentivized test) have significantly different scores on tests without performance-based incentives.

An experimental test of loss aversion and scale compatibility

This paper studies two important reasons why people violate procedure invariance, loss aversion and scale compatibility. The paper extends previous research on loss aversion and scale compatibility by studying loss aversion and scale compatibility simultaneously, by looking at a new decision domain, medical decision analysis, and by examining the effect of loss aversion and scale compatibility on "well-contemplated preferences." We find significant evidence both of loss aversion and scale compatibility. However, the sizes of the biases due to loss aversion and scale compatibility vary over trade-offs and most participants do not behave consistently according to loss aversion or scale compatibility. In particular, the effect of loss aversion in medical trade-offs decreases with duration. These findings are encouraging for utility measurement and prescriptive decision analysis. There appear to exist decision contexts in which the effects of loss aversion and scale compatibility can be minimized and utilities can be measured that do not suffer from these distorting factors.

Trade, migration and regional unemployment

We formulate a dynamic core-periphery model with frictions in the job matching process to study the interplay between trade costs, migration and regional unemploymentin the short- and long-run. We find that the spatial distribution of unemployment mirrors (inversely) the distribution of economic activities. Further, we highlight a contrast between the short-run and the long-run effects of trade-induced migration on regional unemployment. In particular, an inßow of immigrants from the periphery into the core reduces the unemployment gap in the short-run, but exacerbates unemployment disparities in the long-run.

A consistency test of the time trade-off

This paper tests the internal consistency of time trade-off utilities.We find significant violations of consistency in the direction predictedby loss aversion. The violations disappear for higher gauge durations.We show that loss aversion can also explain that for short gaugedurations time trade-off utilities exceed standard gamble utilities. Ourresults suggest that time trade-off measurements that use relativelyshort gauge durations, like the widely used EuroQol algorithm(Dolan 1997), are affected by loss aversion and lead to utilities thatare too high.

Credible redistributive policies and migration across US States

Does worker mobility undermine governments ability to redistribute income? Thispaper analyzes the experience of US states in the recent decades. We build a tractablemodel where both migration decisions and redistribution policies are endogenous. Wecalibrate the model to match skill premium and worker productivity at the state level,as well as the size and skill composition of migration flows. The calibrated modelis able to reproduce the large changes in skill composition as well as key qualitativerelationships of labor flows and redistribution policies observed in the data. Our resultssuggest that regional di¤erences in labor productivity are an important determinantof interstate migration. We use the calibrated model to compare the cross-section ofredistributive policies with and without worker mobility. The main result of the paperis that interstate migration has induced substantial convergence in tax rates acrossUS states, but no race to the bottom. Skill-biased in-migration has reduced the skillpremium and the need for tax-based redistribution in the states that would have hadthe highest tax rates in the absence of mobility.

A test of the predictive validity of non-linear QALY models using time trade-off utilities

This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

A scaled difference chi-square test statistic for moment structure analysis

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks

Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.

On the accuracy of Latin American trade statistics: A nonparametric test for 1925

This paper proposes a nonparametric test in order to establish the level of accuracy of theforeign trade statistics of 17 Latin American countries when contrasted with the trade statistics of the main partners in 1925. The Wilcoxon Matched-Pairs Ranks test is used to determine whether the differences between the data registered by exporters and importers are meaningful, and if so, whether the differences are systematic in any direction. The paper tests for the reliability of the data registered for two homogeneous products, petroleum and coal, both in volume and value. The conclusion of the several exercises performed is that we cannot accept the existence of statistically significant differences between the data provided by the exporters and the registered by the importing countries in most cases. The qualitative historiography of Latin American describes its foreign trade statistics as mostly unusable. Our quantitative results contest this view.

Migration across Spanish provinces: Evidence from the social security records (1978-1992)

This paper uses Social Security records to study internal migrationin Spain. This is the first paper that uses this data source, whichhas some advantages with respect to existing data sources: it includesonly job-seeking migrants and it allows to identify temporary migration. Within the framework of an extended gravity model, we estimate a Generalized Negative Binomial regression on gross migration flows between provinces. We quantify the effect of local labor market imbalances on workers' mobility and discuss the equilibrating role of internal migration in Spain. Our main results show that the effect of employment opportunities have changed after 1984; migrants seem to be more responsive to economic conditions but, consistently with previous studies for the Spanish labor market, the migration response to wage differentials is wrongly signed. Our analysis also confirms the larger internal mobility of highly qualified workers.

What is what?: A simple time-domain test of long-memory vs. structural breaks

This paper proposes a new time-domain test of a process being I(d), 0 < d = 1, under the null, against the alternative of being I(0) with deterministic components subject to structural breaks at known or unknown dates, with the goal of disentangling the existing identification issue between long-memory and structural breaks. Denoting by AB(t) the different types of structural breaks in the deterministic components of a time series considered by Perron (1989), the test statistic proposed here is based on the t-ratio (or the infimum of a sequence of t-ratios) of the estimated coefficient on yt-1 in an OLS regression of ?dyt on a simple transformation of the above-mentioned deterministic components and yt-1, possibly augmented by a suitable number of lags of ?dyt to account for serial correlation in the error terms. The case where d = 1 coincides with the Perron (1989) or the Zivot and Andrews (1992) approaches if the break date is known or unknown, respectively. The statistic is labelled as the SB-FDF (Structural Break-Fractional Dickey- Fuller) test, since it is based on the same principles as the well-known Dickey-Fuller unit root test. Both its asymptotic behavior and finite sample properties are analyzed, and two empirical applications are provided.