On Estimating the Size of the Shadow Economy

As long as it is employed cautiously enough, the model approach is a useful tool to estimate simultaneously the size and the development of the shadow economy in several countries. However, a second method is necessary to calibrate the model. The currency demand approach can lead to highly implausible results; the size of the shadow economy might be largely overestimated. An alternative is the survey method. For real tests of whether a variable has an impact, procedures are necessary that do not use the same variables as those used to construct the indicator. Thus, to make progress in analysing the shadow economy, the model approach has a role to play, but it has to be complemented by other methods employing different data. The currency demand approach cannot be used as long as it employs the same variables for its constructions.     

Banking distress in MENA countries and the role of mergers as a strategic policy to resolve distress

This paper studies banking distress in MENA countries and considers the extent to which mergers are used as a solution for resolving individual banking distress. We use a two-level nested logit model to model the interdependence between merger decisions and the distressed state of banks. Both bank-specific variables and macroeconomic variables are deployed to predict banking distress. In line with other recent papers, we challenge the view that specific bank indicators such as CAMEL category and bank size are more significant determinants of banking distress than macroeconomic variables. A comparison of model fits and out-of-sample forecasts indicates that the unordered NL model statistically outperforms a standard logit model by substantial margins. Our empirical study shows that 67% of the distressed banks in our sample are involved in merger transactions and that weak financial status systematically increases the likelihood of a bank being involved in a merger. Distressed state-owned banks are less likely to be a target of a merger transaction. However, global economic conditions do not significantly affect the decision of distressed banks to initiate a merger policy.     

On the simultaneity of innovations and market structure

This paper examines the determinants of innovations and market structure within a simultaneous framework. From a competitive fringe model, quasi-conditional factor demand functions are derived that explain product and process innovations in terms of factor prices and market structure variables such as relative firm size, market size, and the concentration ratio where the latter set of variables result from the same optimizing process.Empirical evidence is gained from a cross section of 2276 West German firms in the manufacturing sector. In contrast to many other empirical studies, product and process innovations are measured by two dichotomous variables. An exogeneity test for the probit model is worked out and the conditional maximum likelihood estimator that emerges from this test is applied. The results show that simultaneity does matter, even if innovations are explained by market structure variables at the firm level. Accounting for endogeneity and cross-equation restrictions changes the results substantially.     

Revisiting the effects of regional trade agreements on trade flows with proper specification of the gravity model

This paper uses a gravity model to assess ex-post regional trade agreements. The model includes 130 countries and is estimated with panel data over the period 1962-1996. The introduction of the correct number of dummy variables allows for identification of Vinerian trade creation and trade diversion effects, while the estimation method takes into account the unobservable characteristics of each pairs of trade partner countries, the endogeneity of some of the explanatory variables as well as a potential selection bias. In contrast to previous estimates, results show that regional agreements have generated a significant increase in trade between members, often at the expense of the rest of the world.     

知识工作者过度劳动的形成机理探析

近年来,过度劳动在我国呈快速上升趋势,而知识工作者正成为“过劳死”的高危群体.为了有效预防和干预知识工作者过度劳动导致的社会问题,有必要从理论上说明其影响因素和形成机制.本文根据经济学、管理学和心理学的相关理论,将影响因素划分为前因变量、决定变量和调节变量三类,构建过度劳动形成机制的概念模型,从知识工作者的群体特征和个体特质出发,分析各影响因素间的相互关系及其作用机理.总体而言,个人因素和管理因素对知识工作者的过度劳动动机、意愿和行为产生不同程度的直接影响,工作任务因素、社会文化、经济和制度层面等深层次原因构成的环境因素则激励或约束着知识工作者,使其在具备一定过度劳动动机和意愿的情况下,较其他劳动者更容易付出超强度的劳动强度和超长的劳动时间.     

Economic Development Indicators as Determinants of Medal Winning at the Sydney Olympics: An Extreme Bounds Analysis

This paper examines the variables that determine the performance of countries at the Olympic Games as measured by a weighted sum of the medals won at the Sydney 2000 Games. While previous studies have identified the importance of a country's economic size and the resources available to sport, this paper examines nine more variables including the number of athletes representing each nation and some development indicators. Based on 2310 regressions, both traditional and restricted extreme bounds analysis show that only two variables are robust: the number of athletes and national expenditure on health. Thus, the final model recognises four explanatory variables that include these two as well as GDP and population.     

A Base Model for Multifactor Specifications of the Term Structure

In this article, we aim to show that most of the recent multifactor specifications of the term structure can be traced back to a common general equilibrium model, based on an economy of the Cox, Ingersoll and Ross type. This base model of the term structure has a very general form and includes both square root and Gaussian dynamics of the underlying state variables. We establish a direct link among the state variables used in the different specifications of many multifactor models and analyse the structure of the resultant implied relationships. This technique has relevant implications from a practical point of view, as it can allow one to recover from the estimated coefficients of one model the implied value of the coefficients of other models. Moreover, it provides a way of recovering from the term structure the values of such unobservable variables as the real short rate and the expected inflation rate.
(J.E.L.: E43, G12).     

Quantifying the uncertainty of long-term macroeconomic projections

We propose a practical approach to measuring the uncertainty of long-term economic projections. The presented method quantifies the uncertainty of economic variables by using simulations from a multivariate unobserved components model in which variables are formulated as sums of stationary and nonstationary components. The method captures the correlations between both the stationary and nonstationary components of the variables and offers a seamless analysis of short- and long-term uncertainty. Experiments on artificial data demonstrate that, despite its simplicity, the method performs fairly well compared with alternative methods in terms of long-term predictive accuracy and coverage.     

Banking and the role of money in the business cycle

This paper enriches a standard New Keynesian model with a simple banking sector to investigate the role of money in the business cycle. Maximum likelihood estimation of the model suggests that money balances play a significant role in explaining the intertemporal allocation of consumption and the dynamics of inflation as described by the forward-looking IS and Phillips curves. Nonetheless, the responses of the model’s variables to shocks remain qualitatively similar to a model without money, suggesting that the omission of money balances leaves the model’s transmission mechanism unaffected.     

The impacts of bank-specific and macroeconomic variables on the capital adequacy ratio: evidence from Islamic banks

The study investigates the relationship between the capital adequacy ratio (CAR) and different bank-specific and macroeconomic variables for 28 Islamic banks. We document that there is a statistically significant positive relationship between the CAR and the bank-specific and macroeconomic variables. In particular, bank-specific variables such as ROA, ROE, leverage, credit risk and size show a strong association with the CAR, while on the macroeconomic side, inflation, market capitalization and exchange rate have an impact on the average Islamic bank in our sample study. Furthermore, we run another model (equity to assets ratio) as dependent, with similar control variables, and the results reveal that, except for inflation, all the variables that have a significant effect on the CAR also influence the equity to assets ratio.     

Macroeconomic shocks and the probability of being employed

Macroeconomic theories take polar views on the importance of choice versus chance. At the micro level, it seems realistic to assume that both dimensions play a role for individual employment outcomes, although it might be difficult to separate these two effects. Nevertheless the choice and chance dimension are seldom treated symmetrically in models that use micro data. We estimate a logistic model of the probability of being employed among married or cohabitating women that are in the labor force. Besides variables that measure individual characteristics (choice), we allow a full set of indicator variables for observation periods that represent potential effects of aggregate shocks (chance) on job probabilities. To reduce the number of redundant indicator variables automatic model selection is used, and we assess the economic interpretation of the statistically significant indicator variables with reference to a theoretical framework that allows for friction in the Norwegian labor market. In addition, we also estimate models that use female and male unemployment rates as ‘sufficient’ variables for the chance element in individual employment outcomes. Data are for Norway for the period 1988q2–2008q4.     

A simultaneous equations model of the educational process

This paper models the educational process as a system of six simultaneous equations. The endogenous variables include a student's achievement, motivation, expectations, efficacy, and perceived parents' and teachers' expectations. The model also includes forty-eight individual, home, peer, teacher, and school exogenous variables. Using a sample of over sixteen thousand twelfth grade students from the Equality of Educational Opportunity survey, we estimate the model by two-stage least squares and present the reduced form and structural form equations. We find that many educational outputs jointly determine one another. Also, the results suggest that school and teacher variables have important effects on educational outcomes.     

Correcting for the endogeneity of pro-environment behavioral choices in contingent valuation

In contingent valuation studies, observed behavioral choices often enter as independent variables in the willingness to pay function. However, these variables may be endogenously determined when the error term in the behavioral model is correlated with the error term in the willingness to pay model. We investigate the effects of correcting for the endogeneity of a variable, namely membership status in environmental organizations that proxies unobservable characteristics of the respondents. Jointly modeling the membership variable and the willingness to pay response yields an estimate for the effect of the former that contradicts previous findings but is intuitive and agrees with theoretical expectations.     

Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts

Several recent studies have used multivariate unobserved components models to identify the output gap and the non-accelerating inflation rate of unemployment. A key assumption of these models is that one common cycle component, such as the output gap, drives the cyclical fluctuations in all variables included in the model. This article also uses the multivariate approach to estimate the euro area output gap and the trends and cycles in other macroeconomic variables. However, it adopts a flexible way of linking the output gap to the cycle components in the other variables, in that we do not impose any leading or lagging restrictions between cycle components, as has been done in most previous studies. Our approach also allows us to assess the strength of cycle association and cross-correlation among cycle components using the model??s parameter estimates. Finally, we demonstrate that our multivariate model can provide a satisfactory historical output gap estimate and also a ??real-time?? estimate for the aggregate euro area.     

On the information provided by forecasting models

The aim of the paper is to evaluate the information provided by forecasting models that include explanatory variables besides the variables to be forecasted. It is argued that the content of a forecast is a combination of historical information about the variable to be forecasted and theoretical considerations, normally manifested by a model. The historical information is assessed by a time series model for the variable. In order to assess the theoretical information about a variable, one suggests a measure. This measure is based on the improvement of fit to the actual values of the values obtained from the forecasting model in comparison to the values obtained from the time series model. The R² measure, which frequently is used as a measure of the explanatory power of a forecasting model, is critically discussed.     

DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa

Inflation forecasts are a key ingredient for monetary policy-making – especially in an inflation targeting country such as South Africa. Generally, a typical Dynamic Stochastic General Equilibrium (DSGE) only includes a core set of variables. As such, other variables, for example alternative measures of inflation that might be of interest to policy-makers, do not feature in the model. Given this, we implement a closed-economy New Keynesian DSGE model-based procedure which includes variables that do not explicitly appear in the model. We estimate such a model using an in-sample covering 1971Q2 to 1999Q4 and generate recursive forecasts over 2000Q1 to 2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables (both core and nonmodelled) in comparison with forecasts reported by other models such as AR(1). In addition, based on ex-ante forecasts over the period 2012Q1–2013Q4, we find that the DSGE model performs better than the AR(1) counterpart in forecasting actual GDP deflator inflation.     

Testing the exogeneity of economic time series: an application of innovation accounting

This paper proposes and presents an testable sufficient condition for testing the exogeneity of economic time series using Sims' (1980a) innovation accounting within an unconstrained vector autoregressive model. It is demonstrated that if each explanatory variable of a model is sequentially placed in the last position of the ordering of variables during orthogonalization, then strict exogeneity of the dependent variable with respect to each explanatory variable can be tested without any a priorirestrictions. The test is not biased by conditional correlations of other variables included in the model. The empirical demonstration within the VAR framework is based on a set of variables obtained by solving a macroeconomic model.     

Measuring the effects of monetary policy in Pakistan: a factor-augmented vector autoregressive approach

This paper examines the effects of monetary policy on macroeconomic variables in Pakistan’s economy using a data-rich environment. We used the factor-augmented vector autoregressive (FAVAR) methodology, which contains 115 monthly variables for the period 1992:01 to 2010:12. We compared the results of VAR and FAVAR model and the results showed that FAVAR model explains the effects of monetary policy which are consistent with the theory and better than the VAR model. VAR model shows the existence of price puzzle and liquidity puzzle in Pakistan while FAVAR model did not provide any evidence of puzzles. Interest rate negatively influences prices, hence interest rate is a good instrument for controlling inflation in Pakistan but it takes a lag of 5 months. The transmission of monetary policy shock is faster in case of prices as compared to output in Pakistan. FAVAR model supports the effectiveness of interest rate channel in Pakistan.     

潜在变量、宏观变量与动态利率期限结构——基于DRA模型的实证分析

本文从金融-宏观经济学视角出发,运用DRA模型研究了潜在变量、宏观变量与利率期限结构之间的动态关系。通过脉冲响应函数分析了潜在变量与宏观变量之间的相互冲击效应的大小,以及潜在变量、宏观变量对收益率曲线冲击的影响,借助于方差分解量化了潜在变量、宏观变量冲击对收益率曲线预测误差的贡献率,并利用似然比检验,发现中国的收益率曲线与宏观变量之间存在双向的互动关系,但收益率曲线对未来宏观变量的影响更强。     

On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information

Institutions which publish macroeconomic forecasts usually do not rely on a single econometric model to generate their forecasts. The combination of judgements with information from different models complicates the problem of characterizing the predictive density. This article proposes a parametric approach to construct the joint and marginal densities of macroeconomic forecasting errors, combining judgements with sample and model information. We assume that the relevant variables are linear combinations of latent independent two-piece normal variables. The baseline point forecasts are interpreted as the mode of the joint distribution, which has the convenient feature of being invariant to judgments on the balance of risks.