The effects of poor financial information systems on the long term sustainability of local public services. Empirical evidence from the Catalan Municipalities

In this paper we describe the existence of financial illusion in public accountingand we comment on its effects for the future sustainability of local publicservices. We relate these features to the lack of incentives amongst publicmanagers for improving the financial reporting and thus management of publicassets. Financial illusion pays off for politicians and managers since it allowsfor larger public expenditure increases and managerial slack, these beingarguments in their utility functions. This preference is strengthen by the shorttime perspective of politically appointed public managers. Both factors runagainst public accountability. This hypothesis is tested for Spain by using anunique sample. We take data from around forty Catalan local authorities withpopulation above 20,000 for the financial years 1993-98. We build this databasis from the Catalan Auditing Office Reports in a way that it can be linkedto some other local social and economic variables in order to test ourassumptions. The results confirm that there is a statistical relationship between the financialillusion index (FI as constructed in the paper) and higher current expenditure.This reflects on important overruns and increases of the delay in payingsuppliers, as well as on a higher difficulties to face capital finance. Mechanismsfor FI creation have to do among other factors, with delays in paying suppliers(and thereafter higher future financial costs per unit of service), no adequateprovision for bad debts and lack of appropriate capital funding either forreposition or for new equipments. For this, it is crucial to monitor the way inwhich capital transfers are accounted in local public sheet balances. As a result,for most of the Municipalities we analyse, the funds for guaranteeing continuityand sustainability of public services provision are today at risk.Given managerial incentives at present in public institutions, we conclude thatpublic regulation recently enforced for assuring better information systems inlocal public management may not be enough to change the current state of affairs.

Toward a Statistically Robust Assessment of Social and Solidarity Economy Actors. Conceptual Development and Empirical Validation

Many definitions and debates exist about the core characteristics of social and solidarity economy (SSE) and its actors. Among others, legal forms, profit, geographical scope, and size as criteria for identifying SSE actors often reveal dissents among SSE scholars. Instead of using a dichotomous, either-in-or-out definition of SSE actors, this paper presents an assessment tool that takes into account multiple dimensions to offer a more comprehensive and nuanced view of the field. We first define the core dimensions of the assessment tool by synthesizing the multiple indicators found in the literature. We then empirically test these dimensions and their interrelatedness and seek to identify potential clusters of actors. Finally we discuss the practical implications of our model.

The distribution of talent across contests

Do the contests with the largest prizes attract the most able contestants? Towhat extent do contestants avoid competition? In this paper, we show, theoreticallyand empirically, that the distribution of abilities plays a crucial role in determiningcontest choice. Sorting exists only when the proportion of high-ability contestantsis sufficiently small. As this proportion increases, contestants shy away from competitionand sorting decreases, such that, reverse sorting becomes a possibility. Wetest our theoretical predictions using a large panel data set containing contest choiceover three decades. We use exogenous variation in the participation of highly-ablecompetitors to provide empirical evidence for the relationship among prizes, competition,and sorting.

The political cost of reforms

This paper formalizes in a fully-rational model the popular idea that politiciansperceive an electoral cost in adopting costly reforms with future benefits and reconciles it with the evidence that reformist governments are not punished by voters.To do so, it proposes a model of elections where political ability is ex-ante unknownand investment in reforms is unobservable. On the one hand, elections improve accountability and allow to keep well-performing incumbents. On the other, politiciansmake too little reforms in an attempt to signal high ability and increase their reappointment probability. Although in a rational expectation equilibrium voters cannotbe fooled and hence reelection does not depend on reforms, the strategy of underinvesting in reforms is nonetheless sustained by out-of-equilibrium beliefs. Contrary tothe conventional wisdom, uncertainty makes reforms more politically viable and may,under some conditions, increase social welfare. The model is then used to study howpolitical rewards can be set so as to maximize social welfare and the desirability of imposing a one-term limit to governments. The predictions of this theory are consistentwith a number of empirical regularities on the determinants of reforms and reelection.They are also consistent with a new stylized fact documented in this paper: economicuncertainty is associated to more reforms in a panel of 20 OECD countries.

A unifying approach to the empirical evaluation of asset pricing models

Two main approaches are commonly used to empirically evaluate linear factor pricingmodels: regression and SDF methods, with centred and uncentred versions of the latter.We show that unlike standard two-step or iterated GMM procedures, single-step estimatorssuch as continuously updated GMM yield numerically identical values for prices of risk,pricing errors, Jensen s alphas and overidentifying restrictions tests irrespective of the modelvalidity. Therefore, there is arguably a single approach regardless of the factors being tradedor not, or the use of excess or gross returns. We illustrate our results by revisiting Lustigand Verdelhan s (2007) empirical analysis of currency returns.

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.

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.

Econometrics and decision making: Effects of presentation mode

Much of empirical economics involves regression analysis. However, does thepresentation of results affect economists ability to make inferences for decision makingpurposes? In a survey, 257 academic economists were asked to make probabilisticinferences on the basis of the outputs of a regression analysis presented in a standardformat. Questions concerned the distribution of the dependent variable conditional onknown values of the independent variable. However, many respondents underestimateduncertainty by failing to take into account the standard deviation of the estimatedresiduals. The addition of graphs did not substantially improve inferences. On the otherhand, when only graphs were provided (i.e., with no statistics), respondents weresubstantially more accurate. We discuss implications for improving practice in reportingresults of regression analyses.

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.

Making Predictions with Textual Contents

Forecasting real-world quantities with basis on information from textual descriptions has recently attracted significant interest as a research problem, although previous studies have focused on applications involving only the English language. This document presents an experimental study on the subject of making predictions with textual contents written in Portuguese, using documents from three distinct domains. I specifically report on experiments using different types of regression models, using state-of-the-art feature weighting schemes, and using features derived from cluster-based word representations. Through controlled experiments, I have shown that prediction models using the textual information achieve better results than simple baselines such as taking the average value over the training data, and that richer document representations (i.e., using Brown clusters and the Delta- TF-IDF feature weighting scheme) result in slight performance improvements.

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.

Forecasting and turning point predictions in a Bayesian panel VAR model

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.