Economic information versus quality variation in cross-country data

Data quality in the Penn World Tables varies systematically across countries that have different growth rates and are at different stages of economic development, thus introducing measurement error correlated with variables of economic interest. We explore this problem with three examples from the literature, showing that the problem appears to be minor in growth convergence regressions but serious in estimating the effect of income volatility on growth and in a cross-country test of the Permanent Income Hypothesis. The results suggest, at the least, a need for performing appropriate sensitivity tests before drawing conclusions from analyses based on these data. JEL Classification: E21, O47     

Anticipation effects of technological progress on capital accumulation: a vintage capital approach

Due to embodied technological progress new generations of capital goods are more productive. Therefore, in order to study the effects of technological progress, a model must be analyzed in which different generations of capital goods can be distinguished. We determine in what way the firm adjusts current investments to predictions of technological progress. In the presence of market power we show that a negative anticipation effect occurs, i.e. current investments in recent generations of capital goods decline when faster technological progress will take place in the future, because then it becomes more attractive to wait for new generations of capital goods. In case that only investments in new machines are possible, actually a whole wave of anticipation phases arises.     

Economic effects of positive credit information sharing: the case of Korea

In many countries, in addition to negative credit information such as loan default and arrears, positive credit information is also exchanged on a voluntary and reciprocal basis. Employing optimal credit decision models of profit maximizing banks, and utilizing a unique dataset of 2?million consumer loan obligors in Korea, we investigate the economic effects of sharing positive credit information in addition to negative credit information already exchanged. We find that the discriminatory power of the credit scoring model improves significantly. We proceed to investigate the economic effects of the information gap in a competitive credit market by assuming two representative banks that differ only in the level of credit information sharing. The bank that utilizes negative information only suffers from deterioration of the borrower pool and reduced profit, as high credit risk borrowers are more concentrated on this bank due to underpricing of risks. Our finding suggests that banks have incentives to voluntarily participate in the positive information sharing mechanism, since even a small difference in discriminatory power stemming from the information gap may lead to a significant fall in profitability as the distribution of borrower quality changes endogenously due to adverse selection problems.     

Evaluating FOMC forecast ranges: an interval data approach

The Federal Open Market Committee (FOMC) of the U.S. Federal Reserve publishes the range of members’ forecasts for key macroeconomic variables, but not the distribution of forecasts within this range. To evaluate these projections, previous papers compare the midpoint of the range with the realized outcome. This paper proposes an alternative approach to forecast evaluation that takes account of the interval nature of projections. It is shown that using the conventional Mincer–Zarnowitz approach to evaluate FOMC forecasts misses important information contained in the width of the forecast interval. This additional information plays a minor role at short forecast horizons but turns out to be of sometimes crucial importance for longer-horizon forecasts. For 18-month-ahead forecasts, the variation of members’ projections contains information that is more relevant for explaining future inflation than information embodied in the midpoint. Likewise, when longer-range forecasts for real GDP growth and the unemployment rate are considered, the width of the forecast interval comprises information over and above the one given by the midpoint alone.     

Tax policy and investment demand: A vintage approach

The effects of changes intax incentives for investment are investigated for a putty-clay vintage model in which replacement is an economic decision without requiring static expectations or steady-state growth. It is shown that, with a Cobb-Douglas ex ante production function, the effect on output and its price is identical with that in a non-vintage model with the same parameters. The effect on investment and employment is to introduce a long-run cyclical element. Some simulations for UK manufacturing show that even the direction of the short-run effect on investment and employment can be different dates.     

Decomposition of new venture growth into firm age,survey period and vintage effects

Firm data are accumulated on a yearly basis. In view of the linear relationship of firm age?+?foundation year?=?survey year, the fluctuations of firm data classified by age and period cannot be decomposed into age, period and cohort (foundation year) effects. Three decomposition methods are briefly reviewed and applied to Japanese data on new ventures founded since 1995. Regarding sales and employment growth, the age effect is the largest with a downward trend, and the cohort effect is negligible. Regarding labour productivity, the age effect indicates upward movements, and the cohort effect is negligible. The reason of the negligible cohort effect is discussed.     

Endogenous information quality: A job-assignment application

This paper investigates the optimal acquisition of information in a model of job assignment within a firm. We consider a firm with two types of jobs, skilled and unskilled. The firm draws workers randomly from the general population, and a worker is either talented or untalented. Initially, a worker's productivity in the firm is unknown to the worker and the firm. Workers are equally productive in the unskilled job, but talented workers are more productive in the skilled job than in the unskilled job, and untalented workers are more productive in the unskilled job than in the skilled job. Before assigning a worker to a job, the firm can test whether the employee is talented, and the firm is able to choose the accuracy of this test. We assume that the cost of a test is increasing and convex in test accuracy. We show that (1) the accuracy of the firm's test increases with the cost of a mismatched worker; (2) increased optimism about the worker's ability need not lead to less rigorous testing; (3) the probability that a worker is assigned to the skilled job need not increase as the gain from assigning a talented worker to a skilled job increases, or the loss from assigning an untalented worker to a skilled job decreases, or the fraction of the population that is skilled increases; and (4) a longer testing period, allowing as many as two tests of workers, leads the firm to use a less expensive, and less accurate, test initially than when there is only one opportunity to gather information.     

Three macroeconomic syntheses of vintage 1937: Hicks,Haberler, and Lundberg

Abstract

The 1920s and 1930s were years of intensive debate about economic dynamics and stabilisation policies. There was a large variety of explanations of cycles and depressions, and Keynes’ General Theory of Employment, Interest and Money (1936) was pitched against them. In 1937, followed three different attempts to provide synthetic expositions of macroeconomic theory that would deal with the Keynesian challenge: Hicks’ Mr. Keynes and the “Classics”, Haberler's Prosperity and Depression, and Lundberg's Studies in the Theory of Economic Expansion. This paper compares those 1937 syntheses and contrasts them with the “Neoclassical Synthesis” and the current “New Neoclassical Synthesis”.     

Nowcasting Chinese GDP: information content of economic and financial data

This article applies the factor model proposed by Giannone, Reichlin, and Small (2005 Giannone, D., Reichlin, L. and Small, D. 2005. “Nowcasting GDP and inflation: The real time information content of macroeconomic data release”. In Finance and Economic Discussion Series 2005–42, Washington, DC: Board of Governors of the Federal Reserve System.  [Google Scholar]) on a large data set to nowcast (i.e. current-quarter forecast) the annual growth rate of China's quarterly GDP. The data set contains 189 indicator series of several categories, such as prices, industrial production, fixed asset investment, external sector, money market, and financial market. This article also applies Bai and Ng's criteria (2002) to determine the number of common factors in the factor model. The identified model generates out-of-sample nowcasts for China's GDP with smaller mean-squared forecast errors than those of the random walk benchmark. Moreover, using the factor model, we find that interest rate data is the single most important block of information to improve estimates of current-quarter GDP in China. Other important blocks are consumer and retail prices data and fixed asset investment indicators.     

Speed and quality of collective decision making: Imperfect information processing

This paper studies efficient programmed hierarchies as introduced by Radner [The organization of decentralized information processing, Econometrica 61(5) (1993) 1109-1146] in which agents cannot process information perfectly. A group of P identical managers has to make a choice between n alternatives. In order to learn which is the best option, the alternatives have to be compared. The evaluation of an alternative takes time and managers are only able to identify the better one of two alternatives with a positive probability. The skip-level reporting tree proposed by Radner is found to be efficient in terms of the dimensions decision cost, decision delay, and decision quality.     

A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data

This paper documents multivariate forecast disagreement among professional forecasters and discusses implications for models of heterogeneous expectation formation. Disagreement varies over time and is positively correlated with general (economic) uncertainty. The degree to which individual forecasters disagree with the average forecast tends to persist over time. Models of heterogeneous expectation formation can be modified by introducing heterogeneous signal-to-noise ratios to match this feature. Furthermore, disagreement about correlations of different macroeconomic variables is high on average. In general, multivariate forecast data can be used more effectively than it has been to estimate models with heterogeneous expectations and to test the mechanisms used to generate disagreement in these models.     

Structuring technological information for technology roadmapping: data mining approach

Most research on technology roadmapping has focused on its practical applications and the development of methods to enhance its operational process. Thus, despite a demand for well-supported, systematic information, little attention has been paid to how/which information can be utilised in technology roadmapping. Therefore, this paper aims at proposing a methodology to structure technological information in order to facilitate the process. To this end, eight methods are suggested to provide useful information for technology roadmapping: summary, information extraction, clustering, mapping, navigation, linking, indicators and comparison. This research identifies the characteristics of significant data that can potentially be used in roadmapping, and presents an approach to extracting important information from such raw data through various data mining techniques including text mining, multi-dimensional scaling and K-means clustering. In addition, this paper explains how this approach can be applied in each step of roadmapping. The proposed approach is applied to develop a roadmap of radio-frequency identification (RFID) technology to illustrate the process practically.     

Economic uncertainty and corruption: evidence from a large cross-country data set

A vast amount of research has considered numerous causes and correlates of corruption. Also, there have been many studies of the consequences of various forms of uncertainty. However, exploration of the nexus between economic uncertainty and corruption appears scarce. After providing an intuitive and heuristic linkage between general economic uncertainty and corruption, this article uses a large cross-country data set to augment a fairly standard model with simple proxies for uncertainty and to investigate how economic uncertainty might affect the prevalence of corruption. In addition, a quantile-regression framework is used to judge how the strength of various covariates may differ with the level of corruption. Seven main points emerge from the estimates. First, economic uncertainty is associated positively with corruption, and the relation seems to be robust across measures of uncertainty and corruption. Second, quantile-regression estimates indicate considerable parametric heterogeneity across the distribution of corruption. Third, Gross Domestic Product (GDP) per capita has the expected corruption-mitigating role. Fourth, increased political rights and civil liberties also appear to lower corruption. Fifth, greater government consumption is associated with lower corruption. Sixth, while the hyperinflation dummy lacks significance in most OLS regressions, its significance varies across the distribution of corruption. Seventh, neither police force nor government subsidies shows significance, but transition economies have more corruption.     

Building vintage and electricity use: Old homes use less electricity in hot weather

This paper studies whether electricity use in newer or older residential buildings rises more in response to high temperature in a region of Southern California. Peak electricity demand occurs at the highest temperatures which are predicted to increase due to climate change. Understanding how newer buildings differ from older buildings improves forecasts of how peak electricity use will grow over time. Newer buildings are subject to stricter building energy codes, but are larger and more likely to have air conditioning; hence, the cumulative effect is ambiguous. This paper combines four large datasets of building and household characteristics, weather data, and utility data to estimate the electricity–temperature response of different building vintages. Estimation results show that new buildings (1970–2000) have a statistically significantly higher temperature response (i.e., use more electricity) than old buildings (pre1970). Auxiliary regressions with controls for tiered electricity prices, number of bedrooms, income, square footage, central air conditioning, ownership, and type of residential structure partially decompose the effect. Though California has had extensive energy efficiency building standards that by themselves would lower temperature response for new buildings, the cumulative effect of new buildings is an increase in temperature response. As new buildings are added, aggregate temperature response is predicted to increase.     

Information quality choice and information disclosure in oligopoly

In this paper, we provide a framework to analyze the information disclosure and information quality choice in the oligopoly in which one firm has the opportunity to choose her information quality flexibly and then decide her information disclosure rule after she has observed her information.We find that in the Cournot (Bertrand)competition, when the goods are substitutes (complements) and the degree of substitution (complement) is small enough, the firm will choose the maximal information quality. However, if the degree of substitution (complement) is large enough, the information quality is some intermediate value. On the other hand, in the Cournot (Bertrand) competition, when the goods are complements (substitutes), the maximal information quality will be chosen. We also find that the Fully Revealing case in which the probability of information disclosure is one will occur in (i) the Cournot competition with sufficiently small degree of substitution; (ii) the Cournot competition when goods are complements; (iii) the Bertrand competition when goods are substitutes; (iv) the Bertrand competition with sufficiently small degree of complements. Moreover, we show that the No Revealing case in which the probability of information disclosure is zero will never show up.     

会计职业判断与提高会计信息质量

强调会计职业判断，采用国际通行的实质重于形式原则是2001年1月1日开始施行的《企业会计制度》不同于以往会计制度的一个重要方面，它对于发挥会计人员的主观能动性，提高会计信息质量，具有十分重要的意义。然而，在会计实务中，要全面运用会计职业判断还存在许多困难，需要经过长期、多方面的努力，才能提高会计人员的职业判断能力，达到提高会计信息质量的目标。     

Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian consumer inflation (Índice de Preços ao Consumidor Amplo; IPCA). We will compare forecasting models using disaggregated and aggregated data from IPCA over 12 months ahead. We used IPCA in a monthly basis, over the period between January 1996 and March 2012. Out-of-sample analysis will be made through the period of January 2008 to March 2012. The disaggregated models were estimated by Seasonal Autoregressive Integrated Moving Average (SARIMA) and will have different levels of disaggregation from IPCA as groups and items, as well as disaggregation with more economic sense used by Brazilian Central Bank as: (1) services, monitored prices, food and industrials and (2) durables, non-durables, semi-durables, services and monitored prices. Aggregated models will be estimated by time series techniques as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy among models will be made by the selection model procedure known as Model Confidence Set developed by Peter Hansen, Asger Lunde and James Nason. We were able to find evidence of forecast accuracy gains in models using more disaggregated rather than aggregate data.