A comparative study of alternative approaches for common factors identification

Preliminary version

Primary Commodity Prices: Co-movements, Common Factors and Fundamentals

The behavior of commodities is critical for developing and developed countries alike. This paper contributes to the empirical evidence on the co-movement and determinants of commodity prices. Using nonstationary panel methods, we document a statistically significant degree of co-movement due to a common factor. Within a Factor Augmented VAR approach, real interest rate and uncertainty, as postulated by a simple asset pricing model, are both found to be negatively related to this common factor. This evidence is robust to the inclusion of demand and supply shocks, which both positively impact on the co-movement of commodity prices.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Common factors in Latin America's business cycles

This paper constructs new business cycle indices for Argentina, Brazil, Chile, and Mexico based on common dynamic factors extracted from a comprehensive set of sectoral output, external trade, fiscal and financial variables. The analysis spans the 135 years since the insertion of these economies into the global economy in the 1870s. The constructed indices are used to derive a business cyc1e chronology for these countries and characterize a set of new stylized facts. In particular, we show that ali four countries have historically displayed a striking combination of high business cyc1e volatility and persistence relative to advanced country benchmarks. Volatility changed considerably over time, however, being very high during early formative decades through the Great Depression, and again during the 1970s and ear1y 1980s, before declining sharply in three of the four countries. We also identify a sizeable common factor across the four economies which variance decompositions ascribe mostly to foreign interest rates and shocks to commodity terms of trade.

Common factors method to predict the carcass composition tissue in kid goats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Towards a taxonomy of common factors in psychotherapy-results of an expert survey

BACKGROUND: How change comes about is hotly debated in psychotherapy research. One camp considers 'non-specific' or 'common factors', shared by different therapy approaches, as essential, whereas researchers of the other camp consider specific techniques as the essential ingredients of change. This controversy, however, suffers from unclear terminology and logical inconsistencies. The Taxonomy Project therefore aims at contributing to the definition and conceptualization of common factors of psychotherapy by analyzing their differential associations to standard techniques. METHODS: A review identified 22 common factors discussed in psychotherapy research literature. We conducted a survey, in which 68 psychotherapy experts assessed how common factors are implemented by specific techniques. Using hierarchical linear models, we predicted each common factor by techniques and by experts' age, gender and allegiance to a therapy orientation. RESULTS: Common factors differed largely in their relevance for technique implementation. Patient engagement, Affective experiencing and Therapeutic alliance were judged most relevant. Common factors also differed with respect to how well they could be explained by the set of techniques. We present detailed profiles of all common factors by the (positively or negatively) associated techniques. There were indications of a biased taxonomy not covering the embodiment of psychotherapy (expressed by body-centred techniques such as progressive muscle relaxation, biofeedback training and hypnosis). Likewise, common factors did not adequately represent effective psychodynamic and systemic techniques. CONCLUSION: This taxonomic endeavour is a step towards a clarification of important core constructs of psychotherapy. KEY PRACTITIONER MESSAGE: This article relates standard techniques of psychotherapy (well known to practising therapists) to the change factors/change mechanisms discussed in psychotherapy theory. It gives a short review of the current debate on the mechanisms by which psychotherapy works. We provide detailed profiles of change mechanisms and how they may be generated by practice techniques.

Blooms of the cyanobacterium Lyngbya majuscula in coastal Queensland, Australia: disparate sites, common factors

During the last decade there has been a significant rise in observations of blooms of the toxic cyanobacterium, Lyngbya majuscula along the east coast of Queensland, Australia. Whether the increase in cyanobacterial abundance is a biological indicator of widespread water quality degradation or also a function of other environmental change is unknown. A bioassay approach was used to assesses the potential for runoff from various land uses to stimulate productivity of L. majuscula. In Moreton Bay, L. majuscula productivity was significantly (p < 0.05) stimulated by soil extracts, which were high in phosphorus, iron and organic carbon. Productivity of L. majuscula from the Great Barrier Reef was also significantly (p < 0.05) elevated by iron and phosphorus rich extracts, in this case seabird guano adjacent to the bloom site. Hence, it is possible that other L. majuscula blooms are a result of similar stimulating factors (iron, phosphorus and organic carbon), delivered through different mechanisms. (c) 2004 Elsevier Ltd. All rights reserved.

Common and Idiosyncratic Factors of the Exchange Risk Premium in Emerging European Markets

Existing empirical evidence suggests that the Uncovered Interest Rate Parity (UIRP) condition may not hold due to an exchange risk premium. For a panel data set of eleven emerging European economies we decompose this exchange risk premium into an idiosyncratic (country-specific) elements and a common factor using a principal components approach. We present evidence of a stationary idiosyncratic component and nonstationary common factor. This result leads to the conclusion of a nonstationary risk premium for these countries and a violation of the UIRP in the long-run, which is in contrast to previous studies often documenting a stationary premium in developed countries. Furthermore, we report that the variation in the premium is largely attributable to a common factor influenced by economic developments in the United States.

Is there a common factor for vision?

In cognition, common factors play a crucial role. For example, different types of intelligence are highly correlated, pointing to a common factor, which is often called g. One might expect that a similar common factor would also exist for vision. Surprisingly, no one in the field has addressed this issue. Here, we provide the first evidence that there is no common factor for vision. We tested 40 healthy students' performance in six basic visual paradigms: visual acuity, vernier discrimination, two visual backward masking paradigms, Gabor detection, and bisection discrimination. One might expect that performance levels on these tasks would be highly correlated because some individuals generally have better vision than others due to superior optics, better retinal or cortical processing, or enriched visual experience. However, only four out of 15 correlations were significant, two of which were nontrivial. These results cannot be explained by high intraobserver variability or ceiling effects because test-retest reliability was high and the variance in our student population is commensurate with that from other studies with well-sighted populations. Using a variety of tests (e.g., principal components analysis, Bayes theorem, test-retest reliability), we show the robustness of our null results. We suggest that neuroplasticity operates during everyday experience to generate marked individual differences. Our results apply only to the normally sighted population (i.e., restricted range sampling). For the entire population, including those with degenerate vision, we expect different results.

Testing for a Unit Root in Panels with Dynamic Factors

This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asymptotic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.

Constructing common-factor portfolios

In this paper we construct common-factor portfolios using a novel linear transformation of standard factor models extracted from large data sets of asset returns. The simple transformation proposed here keeps the basic properties of the usual factor transformations, although some new interesting properties are further attached to them. Some theoretical advantages are shown to be present. Also, their practical importance is confirmed in two applications: the performance of common-factor portfolios are shown to be superior to that of asset returns and factors commonly employed in the finance literature.

Whole life performance assessment: critical success factors

Whole life costing (WLC) has become the best practice in construction procurement and it is likely to be a major issue in predicting whole life costs of a construction project accurately. However, different expectations from different organizations throughout a project's life and the lack of data, monitoring targets, and long-term interest for many key players are obstacles to be overcome if WLC is to be implemented. A questionnaire survey was undertaken to investigate a set of ten common factors and 188 individual factors. These were grouped into eight critical categories (project scope, time, cost, quality, contract/administration, human resource, risk, and health and safety) by project phase, as perceived by the clients, contractors and subcontractors in order to identify critical success factors for whole life performance assessment (WLPA). Using a relative importance index, the top ten critical factors for each category, from the perspective of project participants, were analyzed and ranked. Their agreement on those categories and factors were analyzed using Spearman's rank correlation. All participants identify “Type of Project” as the most common critical factor in the eight categories for WLPA. Using the relative index ranking technique and weighted average methods, it was found that the most critical individual factors in each category were: “clarity of contract” (scope); “fixed construction period” (time); “precise project budget estimate” (cost); “material quality” (quality); “mutual/trusting relationships” (contract/administration); “leadership/team management” (human resource); and “management of work safety on site” (health and safety). There was relatively a high agreement on these categories among all participants. Obviously, with 80 critical factors of WLPA, there is a stronger positive relationship between client and contactor rather than contractor and subcontractor, client and subcontractor. Putting these critical factors into a criteria matrix can facilitate an initial framework of WLPA in order to aid decision making in the public sector in South Korea for evaluation/selection process of a construction project at the bid stage.