One market, one number? A composite indicator assessment of EU internal market dynamics.

We consider the lack of consensus about an appropriate theoretical framework linking sub-indicators as a defining characteristic of composite indicators. This intrinsic feature implies uncertainties about the appropriate normalisation and aggregation of the raw data. The two are related: index theory offers some valuable guidelines about their connection. Yet these do not fully solve the basic problem of expert disagreement. We embed such (residual) disagreement in the aggregation method itself. Specifically, we apply an impartial benefit-of-the-doubt weighting procedure, where weight restrictions incorporate the available information on experts’ opinions. We apply this procedure to the dynamic performance assessment of EU Internal Market effects, thereby highlighting its capacity to disaggregate member states’ observed performance shifts into changes relative to benchmarks and performance changes of the benchmarks (i.e. catching up versus genuine progress). Our results indicate that the latter factor is more important in explaining the observed progress.Dynamics; Market;

One Market, One Number? A Composite Indicator Assessment of EU Internal Market Dynamics

We consider the lack of consensus about an appropriate theoretical framework linking sub-indicators as a defining characteristic of composite indicators. This intrinsic feature implies uncertainties about the appropriate normalisation and aggregation of the raw data. The two are related: index theory offers some valuable guidelines about their connection. Yet these do not fully solve the basic problem of expert disagreement. We embed such (residual) disagreement in the aggregation method itself. Specifically, we apply an impartial benefit-of-the-doubt weighting procedure, where weight restrictions incorporate the available information on experts’ opinions. We apply this procedure to the dynamic performance assessment of EU Internal Market effects, thereby highlighting its capacity to disaggregate member states’ observed performance shifts into changes relative to benchmarks and performance changes of the benchmarks (i.e. catching up versus genuine progress). Our results indicate that the latter factor is more important in explaining the observed progress.composite indicators, aggregation, weighting, Internal Market

The elasticity of trade : estimates and evidence

Quantitative results from a large class of structural gravity models of international trade depend critically on a single parameter governing the elasticity of trade with respect to trade frictions. We provide a new method to estimate this elasticity and illustrate the merits of our approach relative to the estimation strategy of Eaton and Kortum (2002). We employ this method on data for 123 developed and developing countries for the year 2004 using new disaggregate price and trade flow data. Our benchmark estimate for all countries is approximately 4.5, nearly 50 percent lower than the alternative estimation strategy would suggest. This difference implies a doubling of the measured welfare costs of autarky across a large class of widely used trade models

Gradient descent for sparse rank-one matrix completion for crowd-sourced aggregation of sparsely interacting workers

We consider worker skill estimation for the singlecoin Dawid-Skene crowdsourcing model. In practice skill-estimation is challenging because worker assignments are sparse and irregular due to the arbitrary, and uncontrolled availability of workers. We formulate skill estimation as a rank-one correlation-matrix completion problem, where the observed components correspond to observed label correlation between workers. We show that the correlation matrix can be successfully recovered and skills identifiable if and only if the sampling matrix (observed components) is irreducible and aperiodic. We then propose an efficient gradient descent scheme and show that skill estimates converges to the desired global optima for such sampling matrices. Our proof is original and the results are surprising in light of the fact that even the weighted rank-one matrix factorization problem is NP hard in general. Next we derive sample complexity bounds for the noisy case in terms of spectral properties of the signless Laplacian of the sampling matrix. Our proposed scheme achieves state-of-art performance on a number of real-world datasets.Published versio

The Elasticity of Trade: Estimates and Evidence

Quantitative results from a large class of international trade models depend critically on the elasticity of trade with respect to trade frictions. We develop a simulated method of moments estimator to estimate this elasticity from disaggregate price and trade-flow data using the Ricardian model. We motivate our estimator by proving that the estimator developed in Eaton and Kortum (2002) is biased in any finite sample. We quantitatively show that the bias is severe and that the data requirements necessary to eliminate it in practice are extreme. Applying our estimator to new disaggregate price and trade-flow data for 123 countries in the year 2004 yields a trade elasticity of roughly four, nearly fifty percent lower than Eaton and Kortum’s (2002) approach. This difference doubles the welfare gains from international trade.elasticity of trade, bilateral, gravity, price dispersion, indirect inference

The Elasticity of Trade: Estimates & Evidence

Quantitative results from a large class of structural gravity models of international trade depend critically on a single parameter governing the elasticity of trade with respect to trade frictions. We provide a newmethod to estimate this elasticity and illustrate themerits of our approach relative to the estimation strategy of Eaton and Kortum (2002). We employ this method on data for 123 developed and developing countries for the year 2004 using new disaggregate price and trade flowdata. Our benchmark estimate for all countries is approximately 4.5, nearly 50 percent lower than the alternative estimation strategywould suggest. This difference implies a doubling of the measured welfare costs of autarky across a large class of widely used trade models.elasticity of trade, bilateral; gravity; price dispersion; indirect inference.

The European venture capital and private equity country attractiveness index(es)

We calculate composite indexes to compare the attractiveness of 25 European countries for institutional investments into the Venture Capital and Private Equity asset class. To achieve this we use 42 different criteria and propose an aggregation structure that allows for benchmarking on more granular levels. The United Kingdom leads our ranking, followed by Ireland, Denmark, Sweden and Norway. While Germany is slightly above the average European attractiveness level, the scores for France, Italy, Spain, and Greece are rather disappointing. Our analyses reveal that while the United Kingdom is similar to the other European countries with respect to many criteria, there are two major differences which ultimately affect its attractiveness: its investor protection and corporate governance rules; and the size and liquidity of its capital market. The state of the capital market is likewise a proxy for the professionalism of the financial community, deal flow and exit opportunities. We determine a reasonable correlation between our attractiveness index scores and actual Venture Capital and Private Equity fundraising activities and prove the robustness of our calculations. Our findings across all the European countries suggest that while investor protection and capital markets are in fact very important determinants of attractiveness, there are numerous other criteria to consider.Venture Capital; Private Equity; Alternative Asset; International Asset Allocation;

A Modular Programmable CMOS Analog Fuzzy Controller Chip

We present a highly modular fuzzy inference analog CMOS chip architecture with on-chip digital programmability. This chip consists of the interconnection of parameterized instances of two different kind of blocks, namely label blocks and rule blocks. The architecture realizes a lattice partition of the universe of discourse, which at the hardware level means that the fuzzy labels associated to every input (realized by the label blocks) are shared among the rule blocks. This reduces the area and power consumption and is the key point for chip modularity. The proposed architecture is demonstrated through a 16-rule two input CMOS 1-μm prototype which features an operation speed of 2.5 Mflips (2.5×10^6 fuzzy inferences per second) with 8.6 mW power consumption. Core area occupation of this prototype is of only 1.6 mm 2 including the digital control and memory circuitry used for programmability. Because of the architecture modularity the number of inputs and rules can be increased with any hardly design effort.This work was supported in part by the Spanish C.I.C.Y.T under Contract TIC96-1392-C02- 02 (SIVA)

To Aggregate, Pool, or Neither: Testing the Rational Expectations Hypothesis Using Survey Data

It is well known that even if all forecasters are rational, estimated coefficients in unbiasedness regressions using consensus forecasts are inconsistent because forecasters have private information. However, if all forecasters face a common realization, pooled estimators are also inconsistent. In contrast, we show that when predictions and realizations are integrated and cointegrated, micro-homogeneity ensures that consensus and pooled estimators are consistent. Therefore, contrary to claims in the literature, in the absence of micro-homogeneity, pooling is not a solution to the aggregation problem. We reject micro-homogeneity for a number of forecasts from the Survey of Professional Forecasters. Therefore, for these variables unbiasedness can only be tested at the individual level.Rational Expectations, Micro-homogeneity, Heterogeneity Bias, Aggregation Bias, Survey Forecasts