The challenge of representative design in psychology and economics

The demands of representative design, as formulated by Egon Brunswik (1956), set a high methodological standard. Both experimental participants and the situations with which they are faced should be representative of the populations to which researchers claim to generalize results. Failure to observe the latter has led to notable experimental failures in psychology from which economics could learn. It also raises questions about the meaning of testing economic theories in abstract environments. Logically, abstract tests can only be generalized to abstract realities and these may or may not have anything to do with the empirical realities experienced by economic actors.

Ethics and creative accounting: Some empirical evidence on accounting for intangibles in Spain

Recent research shows that financial reports are losing relevance. Mainly thisis due to the growing strategic importance of intangible assets in theperformance of a company. A possible solution is to modify accounting standardsso that statements include more self-generated intangible assets, taking intoaccount with their inherent risk and difficulty of valuation. We surveyed loanofficers who were asked to assess the credit-worthiness of a hypotheticalcompany. The only information given was a simplified version of financialstatements. Half the group got statements where research and development costshad been capitalized. The other half got statements in which these costs hadbeen treated as an expense. The findings show that capitalization wassignificantly more likely to attract a positive response to a loan request. Thepaper raises the question of whether accounting for intangibles might providemanagers with one more creative accounting technique and, in consequence, itsethical implications.

Adaptive model selection using empirical complexities

Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

Investigating barriers in HIV-testing oncology patients. The IBITOP study: phase I.

BACKGROUND: Since the advent of combined antiretroviral therapy (ART), the incidence of non-AIDS-defining cancers (non-ADCs) among HIV-positive patients is rising. We previously described HIV testing rates of <5% in our oncology centre, against a local HIV prevalence of 0.4% (1). We have since worked with the Service of Oncology to identify, how HIV testing can be optimized, we have conducted a study on investigating barriers in HIV-testing oncology patients (IBITOP) among treating oncologists and their patients. METHODS: After an initial two-month pilot study to examine feasibility (2), we conducted the first phase of the IBITOP study between 1st July and 31st October 2013. Patients of unknown HIV status, newly diagnosed with solid-organ non-AIDS-defining cancer, and treated at Lausanne University Hospital were invited to participate. Patients were offered HIV testing as a part of their initial oncology work-up. Oncologist testing proposals and patient acceptance were the primary endpoints. RESULTS: Of 235 patients with a new oncology diagnosis, 10 were excluded (7 with ADCs and 3 of known HIV-positive status). Mean age was 62 years; 48% were men and 71% were Swiss. Of 225 patients, 75 (33%) were offered HIV testing. Of these, 56 (75%) accepted, of whom 52 (93%) were tested. A further ten patients were tested (without documentation of being offered a test), which gave a total testing rate of 28% (62/225). Among the 19 patients who declined testing, reasons cited included self-perceived absence of HIV risk, previous testing and palliative care. Of the 140 patients not offered HIV testing and not tested, reasons were documented for 35 (25%), the most common being previous testing and follow-up elsewhere. None of the 62 patients HIV tested had a reactive test. CONCLUSIONS: In this study, one third of patients seen were offered testing and the HIV testing rate was fivefold higher than that of previously observed in this service. Most patients accepted testing when offered. As HIV-positive status impacts on the medical management of cancer patients, we recommend that HIV screening should be performed in settings, where HIV prevalence is >0.1%. Phase II of the IBITOP study is now underway to explore barriers to HIV screening among oncologists and patients following the updated national HIV testing guidelines which recommend testing in non-ADC patients undergoing chemotherapy.

Social spending and demographics: The role of public policies in the intergenerational redistribution of income. Empirical evidence from Spain and Catalonia

The demographic shift underway in Southern Europe requires a revision of some of thefundamental principles of the traditional welfare state. We analyze the evolution of several aspects of welfare and social expenditure over the last two decades. We find that in the context of the present demographic changes and real estate boom current social and pension policy leads to a new distribution of benefits and burdens which is highly intergenerationally unequal. We argue for a revised definition of public policy based on Musgrave's proposition as a possible rule for an intergenerationally fair distribution.

Did colonization matter for growth? An empirical exploration into the historical causes of Africa's underdevelopment

We investigate the impact of 20th--century European colonizationon growth in Africa. We find that in the 1960--88 period growth has beenfaster for dependencies than for colonies; for British and Frenchcolonies than for Portuguese, Belgian and Italian ones; and for countrieswith less economic penetration during the colonial period. On average,African growth accelerates after decolonization. Proxies for colonialheritage add explanatory power to growth regressions and make indicatorsfor human capital, political and ethnic instability lose significance.Colonial variables capture the same effects of a sub--Saharan dummy andreduce its significance when jointly included in a cross sectionalregression with 98 countries.

University admission marks in Catalonia: Some highlights from the empirical research

The results of the examinations taken by graduated high school studentswho want to enrol at a Catalan university are here studied. To do so,the authors address several issues related to the equity of the system:reliability of grading, difficulty and discrimination power of the exams.The general emphasis is put upon the concurrent research and empiricalevidence about the properties of the examination items and scores. Aftera discussion about the limitations of the exams' format and appropriatenessof the instruments used in the study, the article concludes with somesuggestions to improve such examinations.

An empirical evaluation of small area estimators

This paper investigates the comparative performance of five small areaestimators. We use Monte Carlo simulation in the context of boththeoretical and empirical populations. In addition to the direct andindirect estimators, we consider the optimal composite estimator withpopulation weights, and two composite estimators with estimatedweights: one that assumes homogeneity of within area variance andsquare bias, and another one that uses area specific estimates ofvariance and square bias. It is found that among the feasibleestimators, the best choice is the one that uses area specificestimates of variance and square bias.

The economic effects of the Protestant Reformation: Testing the Weber hypothesis in the German Lands

Many theories, most famously Max Weber s essay on the Protestant ethic, have hypothesizedthat Protestantism should have favored economic development. With their considerablereligious heterogeneity and stability of denominational affiliations until the 19th century, theGerman Lands of the Holy Roman Empire present an ideal testing ground for this hypothesis.Using population figures in a dataset comprising 272 cities in the years 1300 1900, I find no effectsof Protestantism on economic growth. The finding is robust to the inclusion of a varietyof controls, and does not appear to depend on data selection or small sample size. In addition,Protestantism has no effect when interacted with other likely determinants of economic development.I also analyze the endogeneity of religious choice; instrumental variables estimates ofthe effects of Protestantism are similar to the OLS results.

R&D cooperation and spillovers: Some empirical evidence

This paper provides some first empirical evidence on the relationshipbetween R&D spillovers and R&D cooperation. The results suggest disentangling different aspects of know-how flows. Firms which rate incoming spillovers more importantly and who can limit outgoing spillovers by a more effective protection of know-how, are more likely to cooperate in R&D. Our analysis also finds that cooperating firms have higher incoming spillovers and higher protection of know-how, indicating that cooperation may serve as a vehicle to manage information flows. Our results thus suggest that on the one hand the information sharing and coordination aspects of incoming spillovers are crucial in understanding cooperation, while on the other hand, protection against outgoing spillovers is important for firms to engage in stable cooperative agreements by reducing free-rider problems. Distinguishing different types of cooperative partners reveals that while managing outgoing spillovers is less critical in alliances with non-commercial research partners than between vertically related partners, the incoming spillovers seem to be more critical in understanding the former type of R&D cooperation.

Gender specialization in households: An empirical analysis

This paper studies the effect of parental education on the educational attainmentof children in the US for cohorts born after 1910. Importantly, we allow for cohort-specificdifferences by gender. Our estimates show that paternal education has been more importantfor the attainment of male children (paternal specialization on sons). However, maternalspecialization (on daughters) seems to have appeared only for cohorts born after 1955. Weinterpret these results as evidence that fathers are more important role models for sonswhile mothers are a more important reference for daughters. We argue that our results arerobust to the presence of hereditary unobserved ability and conjecture that both types ofgender specialization may have been present in earlier cohorts too.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.