Quasi-integration in less-than-truckload trucking

This work studies the organization of less-than-truckload trucking from a contractual point of view. We show that the huge number of owner-operators working in the industry hides a much less fragmented reality. Most of those owner-operators are quasi-integrated in higher organizational structures. This hybrid form is generally more efficient than vertical integration because, in the Spanish institutional environment, it lessens serious moral hazard problems, related mainly to the use of the vehicles, and makes it possible to reach economies of scale and density. Empirical evidence suggests that what leads organizations to vertically integrate is not the presence of such economies but hold-up problems, related to the existence of specific assets. Finally, an international comparison hints that institutional constraints are able to explain differences in the evolution of vertical integration across countries.

Earnings management and audit adjustments: An empirical study of IBEX 35 constituents

Doubts about the reliability of a company's qualitative financial disclosure increase market participant expectations from the auditor's report. The auditing process is supposed to serve as a monitoring device that reduces management incentives to manipulate reported earnings. Empirical research confirms that it could be an efficient device under some circumstancesand recognizes that our estimates of the informativeness of audit reports are unavoidably biased (e.g., because of a client's anticipation of the auditing process). This empirical study supports the significant role of auditors in the financial market, in particular in the prevention of earnings management practice. We focus on earnings misstatements, which auditors correct with anadjustment, using a sample of past and current constituents of the benchmark market index in Spain, IBEX 35, and manually collected audit adjustments reported over the 1997-2004 period (42 companies, 336 annual reports, 75 earnings misstatements). Our findings confirm that companies more often overstate than understate their earnings. An investor may foresee earningsmisreporting, as manipulators have a similar profile (e.g., more leveraged and with lower sales). However, he may receive valuable information from the audit adjustment on the size of earnings misstatement, which can be significantly large (i.e., material in almost all cases). We suggest that the magnitude of an audit adjustment depends, other things constant, on annual revenues and free cash levels. We also examine how the audit adjustment relates to the observed market price, trading volume and stock returns. Our findings are that earnings manipulators have a lower price and larger trading volume compared to their rivals. Their returns are positively associated with the magnitude of earnings misreporting, which is not consistent with the possible pricing of audit information.

Testing for convergence clubs in income per-capita: A predictive density approach

The paper proposes a technique to jointly test for groupings of unknown size in the cross sectional dimension of a panel and estimates the parameters of each group, and applies it to identifying convergence clubs in income per-capita. The approach uses the predictive density of the data, conditional on the parameters of the model. The steady state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of incomeper-capita of OECD countries has two poles of attraction and each grouphas clearly identifiable economic characteristics.

Asymptotic behaviour of the density in a parabolic SPDE

Consider the density of the solution $X(t,x)$ of a stochastic heat equation with small noise at a fixed $t\in [0,T]$, $x \in [0,1]$.In the paper we study the asymptotics of this density as the noise is vanishing. A kind of Taylor expansion in powers of the noiseparameter is obtained. The coefficients and the residue of the expansion are explicitly calculated.In order to obtain this result some type of exponential estimates of tail probabilities of the difference between the approximatingprocess and the limit one is proved. Also a suitable local integration by parts formula is developped.

Value and depreciation of mineral resources over the very long run: An empirical contrast of different methods

The paper contrasts empirically the results of alternative methods for estimating thevalue and the depreciation of mineral resources. The historical data of Mexico andVenezuela, covering the period 1920s-1980s, is used to contrast the results of severalmethods. These are the present value, the net price method, the user cost method andthe imputed income method. The paper establishes that the net price and the user costare not competing methods as such, but alternative adjustments to different scenariosof closed and open economies. The results prove that the biases of the methods, ascommonly described in the theoretical literature, only hold under the most restrictedscenario of constant rents over time. It is argued that the difference between what isexpected to happen and what actually did happen is for the most part due to a missingvariable, namely technological change. This is an important caveat to therecommendations made based on these models.

Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

Measuring intangibles' productivity. Empirical evidence from Spanish firms

As companies and shareholders begin to note the potential repercussions of intangible assets uponbusiness results, the inability of the traditional financial statement model to reflect these new waysof creating business value has become evident. Companies have widely adopted newmanagement tools, covering in this way the inability of the traditional financial statement model toreflect these new ways of creating business value.However, there are few prior studies measuring on a quantifiable manner the level of productivityunexplained in the financial statements. In this study, we measure the effect of intangible assets onproductivity using data from Spanish firms selected randomly by size and sector over a ten-yearperiod, from 1995 to 2004. Through a sample of more than 10,000 Spanish firms we analyse towhat extent labour productivity can be explained by physical capital deepening, by quantifiedintangible capital deepening and by firm s economic efficiency (or total factor productivity PTF).Our results confirm the hypothesis that PTF weigh has increased during the period studied,especially on those firms that have experienced a significant raise in quantified intangible capital,evidencing that there are some important complementary effects between capital investment andintangible resources in the explanation of productivity growth. These results have significantdifferences considering economic sector and firm s dimension.

An assessment of empirical Bayes and composite estimators for small areas

We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the area-level means can be inefficient.

The minimax distortion redundancy in empirical quantizer design

We obtain minimax lower and upper bounds for the expected distortionredundancy of empirically designed vector quantizers. We show that the meansquared distortion of a vector quantizer designed from $n$ i.i.d. datapoints using any design algorithm is at least $\Omega (n^{-1/2})$ awayfrom the optimal distortion for some distribution on a bounded subset of${\cal R}^d$. Together with existing upper bounds this result shows thatthe minimax distortion redundancy for empirical quantizer design, as afunction of the size of the training data, is asymptotically on the orderof $n^{1/2}$. We also derive a new upper bound for the performance of theempirically optimal quantizer.

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.

Agglomeration-effects in Europe

The paper estimates agglomeration-effects for France, Germany, Italy, Spain, and the UK. Estimation takes into account endogeneity of the spatial distribution ofemployment and spatial fixed-effects. Empirical resultssuggest that agglomeration-effects in these Europeancountries are only slightly smaller than agglomeration-effects in the US: the estimated elasticity of average-labor-productivity with respect to employment-density is 4.5 percent compared to 5 percent in the US.

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.

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.