Search

In this paper, we construct a quality-adjusted rent index for the office market in Oslo. Commonly used rent indices are based on average developments or expert opinions. Such indices often suffer from compositional biases or low data coverage. Using detailed data from more than 16,000 rental contracts, we show that compositional biases can have a large impact on rental price developments. By adding building fixed effects to a standard hedonic regression model, we show that the explanatory power increases considerably. Furthermore, indices controlling for micro-location portray a different picture of rent developments than indices that do not take this into account. We also document a considerable rent premium for proximity to a metro station. Finally, we exploit information on contract signature date and find that a more timely detection of turning-points can be achieved by using the signature date instead of the more typically used start date of the lease. The financial system is heavily exposed towards the commercial real estate market and timely detection of turning-points is of major importance to policymakers.

We use China’s large-scale reform of state-owned enterprises (SOE) in the late 1990s as a natural experiment to identify and quantify the importance of precautionary savings for wealth accumulation. Before the reform, SOE workers enjoyed the same job security as government employees. After the reform, a cumulative of over 35 million SOE workers have been laid off, although government employees kept their “iron rice bowl.” The change in unemployment risks for SOE workers relative to that of government employees before and after the reform provides a clean identification of income uncertainty that helps us estimate the importance of precautionary savings. In our estimation, we correct a self-selection bias in occupational choices and we disentangle the effects of uncertainty from pessimistic outlook. We obtain evidence that precautionary savings contribute to about one-third of the wealth accumulations for SOE workers between 1995 and 2002. Precautionary savings motive is thus an important factor that drives the observed rising Chinese saving rate.

The German start-up subsidy (SUS) program for the unemployed has recently undergone a major make-over, altering its institutional setup, adding an additional layer of selection and leading to ambiguous predictions of the program’s effectiveness. Using propensity score matching (PSM) as our main empirical approach, we provide estimates of long-term effects of the post-reform subsidy on individual employment prospects and labor market earnings up to 40 months after entering the program. Our results suggest large and persistent long-term effects of the subsidy on employment probabilities and net earned income. These effects are larger than what was estimated for the pre-reform program. Extensive sensitivity analyses within the standard PSM framework reveal that the results are robust to different choices regarding the implementation of the weighting procedure and also with respect to deviations from the conditional independence assumption. As a further assessment of the results’ sensitivity, we go beyond the standard selection-on-observables approach and employ an instrumental variable setup using regional variation in the likelihood of receiving treatment. Here, we exploit the fact that the reform increased the discretionary power of local employment agencies in allocating active labor market policy funds, allowing us to obtain a measure of local preferences for SUS as the program of choice. The results based on this approach give rise to similar estimates. Thus, our results indicating that SUS are still an effective active labor market program after the reform do not appear to be driven by “hidden bias”.

Banks have substantial exposures to commercial real estate (CRE). Rental prices are important for CRE companies’ debt-service capacity, which in turn affects the risk of future bank losses. In this paper, we estimate error correction models (ECMs) to determine the main drivers of office rents in Oslo and to detect deviations in rents from their estimated long-run equilibrium. We find that employment and stock of offices are important explanatory variables. Moreover, our results show that rents have followed their estimated equilibrium closely and have re-adjusted quickly in periods of deviation.

First order conditions from the dynamic optimization problems of consumers and firms are important tools in empirical macroeconomics. When estimated on micro-data these equations are typically linearized so standard IV or GMM methods can be employed to deal with the measurement error that is endemic to survey data. However, it has recently been argued that the approximation bias induced by linearization may be worse than the problems that linearization is intended to solve. This paper explores this issue in the context of consumption Euler equations. These equations form the basis of estimates of key macroeconomic parameters: the elasticity of inter-temporal substitution (EIS) and relative prudence. We numerically solve and simulate 6 different life-cycle models, and then use the simulated data as the basis for a series of Monte Carlo experiments in which we consider the validity and relevance of conventional instruments, the consequences of different data sampling schemes, and the effectiveness of alternative estimation strategies. The first-order Euler equation leads to biased estimates of the EIS, but that bias is perhaps not too large when there is a sufficient time dimension to the data, and sufficient variation in interest rates. A sufficient time dimension can only realistically be achieved with a synthetic cohort. Estimates are unlikely to be very precise. Bias will be worse the more impatient agents are. The second order Euler equation suffers from a weak instrument problem and offers no advantage over the first-order approximation.

We present new evidence about the relationship between military conflict and city population growth in Europe from the fall of Charlemagne’s empire to the start of the Industrial Revolution. Military conflict was a main feature of European history. We argue that cities were safe harbors from conflict threats. To test this argument, we construct a novel database that geocodes the locations of 1,091 conflicts and 676 cities between 800 and 1799. We find a significant, positive, and robust relationship that runs from conflict exposure to city population growth. Our analysis suggests that military conflict played a key role in the rise of urban Europe.

Based on its outward-oriented development strategy, respectable growth, increased integration into world trade and financial markets, and imperfect though vibrant and wide-based democracy, Turkey is often cited as a development model for other countries in the region and elsewhere. Countering this positive picture of the Turkish economy over the last two decades, however, is the incompleteness of its reform process: the boom-bust nature of its growth, persistently high inflation, delays in privatising state-owned enterprises, and high and persistent government budget deficits. In January 2000 Turkey embarked on an ambitious IMF-backed stabilization program designed to correct the weaknesses in its economy, and, in particular, to reduce inflation to single digits by the end of 2002. Since then, though, Turkey has experienced two financial crises and redesigned its stabilization program to bring inflation down more gradually. This collection analyzes the nature of Turkey's inflation and the likely costs and benefits of disinflation.

The market for modern Indian art is an emerging art market, having come into a proper existence only in the late 1990s. This market saw tremendous growth in its initial years and then a downturn that started around 2007-2008. Using data from auctions conducted by a major Indian art auctioneer, we estimate via hedonic regression a price index for paintings and drawings by Indian artists sold during 2000-2013. We are able to thus estimate a rate of return on Indian art as an investment and also shed light on what drives the price of a painting in the Indian market. In doing so, we document quantitatively the extent of the rise and fall in Indian art prices. We also distinguish empirically two segments in the Indian art market, namely modern painters and contemporary painters, who appear to command different prices at auction. We find a positive and statistically significant relationship between the state of the Indian stock market and art auction prices. Finally, we use our econometric results to construct a ranking of Indian painters in terms of the market prices for their work.

We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. To improve out-of-sample prediction accuracy, we propose a method of combining the underlying models via linear regression. Our method is robust to a large number of regressors; scales easily to very large data sets; combines model selection and estimation; and can flexibly approximate arbitrary non-linear functions. We illustrate our method using a standard scanner panel data set and find that our estimates are considerably more accurate in out-of-sample predictions of demand than some commonly used alternatives.

This paper investigates the relationship between gold price growth, oil price shocks, and stock price index in the GCC countries over the period 2006-2008 using daily data. We apply hidden cointegration technique which identifies asymmetry of the cointegrating vectors between components (cumulative positive and negative changes) of the series. The results suggest that there is no link between stock price, gold price growth and oil price shocks. Our findings imply that stock market performance cannot forecast and be forecasted by oil and gold prices. Thus, the possibility of arbitrage is ruled out and the six GCC equity markets can be considered as informationally efficient with respect to oil and gold prices. This has important policy implications for domestic and foreign institutional investors and portfolio managers operating in the Gulf region since our finding can aid in the structuring of coherent trading portfolios in case of equity markets’ turmoil. - Questo lavoro esamina la relazione tra l’aumento del prezzo dell’oro, gli shock del prezzo del petrolio e gli indici azionari nei paesi del Golfo nel periodo 2006-2008 attraverso l’utilizzo di dati giornalieri. Viene applicata una tecnica di cointegrazione nascosta che identifica le asimmetrie dei vettori di cointegrazione tra le componenti (sia di segno positivo che negativo) della serie. I risultati suggeriscono che non c’è relazione tra indici azionari, crescita del prezzo dell’oro e shock nel prezzo del petrolio. Così la possibilità di arbitraggio è esclusa e i sei mercati azionari dei paesi del Golfo possono essere considerati informativamente efficienti in rapporto ai prezzi del petrolio e dell’oro. Ciò comporta implicazioni importanti sia per gli investitori nazionali che per quelli stranieri e per gli operatori di borsa che operano nella regione del Golfo, in quanto le evidenze riscontrate in questo studio possono aiutare a strutturare coerenti portfogli di trading in caso di volatilità nei mercati azionari.

Countries from CEE countries (Bulgaria, Croatia, Czech Republic, Estonia, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia) experienced systemic banking crisis during the recent turbulence on financial markets. Financial crisis can be very costly due to output losses during and after the crash. This article reviews the methodology for estimating the output losses for this particular group of countries recently affected by adverse economic and financial conditions. This study extend the analyses in two directions: first applying a Hodrick-Prescott filter for various lengths e.g. 10 years, 15 years and 20 years and then using the method proposed by Abiad et al (2009) and establishing the counterfactual trend, ignoring the past 3 years before the beginning of the crisis.

Cost reduction, productivity increase and creating value for the client are just a few of the arguments that managers use when they adopt Lean philosophy. Businesses’ concern is to create products that have value in the eyes of the client, continuously analyzing the existing value stream in order to improve it. Value stream mapping (VSM) is a technique used to visually present the chain of processes, within the company, necessary to obtain the product. Due to the many advantages and to the ease of use experienced by Toyota since the ’80, VSM use has constantly increased as this activity improvement technique was discovered by managers. The article presents a case study of the application of VSM in footwear industry.

The paper investigates how entrepreneurial activity depends on economic development, measured by GDP per capita. The empirical analysis is based on GEM yearly data on 65 countries for the period from 2001 to 2011. We use nonparametric approach to show that variation in entrepreneurial activity across countries can be explained by U-shaped relationship, the hypothesis of L-shaped relationship is rejected. At the same time the analysis does not reveal any significant relationship between the variables in time within one particular country.

Election forecasting is an expanding domain within political science, moving from the outer edges (as a novelty pursued by a few ‘quants’) toward the mainstream of the discipline. Amongst the most high profile of election forecasting techniques are prediction markets and vote-intention polls. While the weight of scholarly opinion appears to favour prediction markets over polls for election forecasting, there remain challengers and critics. This article joins with the challengers and the critics, looking at whether this ‘horse race’ competition between election forecasting approaches is valid. Using data from the 2013 Australian federal election, we conclude such comparisons-of-forecasts are misplaced in the Australian context, as prediction markets and vote-intention polls appear to be independent of each other given information from one appears to have no impact on the other.

En este artículo se analiza la convergencia de precios entre las principales ciudades de México, utilizando pruebas de raíz unitaria con datos panel. Si las deviaciones de precios son estacionarias, se dice que existe convergencia de precios e integración de los mercados. Los resultados indican que la desviaciones de precios respecto a la ciudad numeraria son transitorias (no permanentes) y, por lo tanto, tienden a regresar a su valor medio o de equilibro de largo plazo.

The aim of this work is to determine the influence that exports of footwear industry have on the turnover of the sector. In the work, a period of 9 years is taken into consideration: from 2004 to 2012, establishing an econometric model of analysis of the connection between the turnover and direct exports of footwear industry in Romania. Based on the analyzed empirical data, the work answers to the following question: what is the influence that exports of footwear industry have on sector’s turnover? In addition to specifying the econometric model which describes the connection between the two variables, we also test the validity of the model and the intensity of the connection between the two variables.

Die Öffentlichkeit hat ein Interesse zu wissen, ob politische Maßnahmen die mit ihnen verfolgten Ziele wirksam und wirtschaftlich erreichen. In empirischen Studien, die als Grundlage für evidenzbasierte Wirtschaftspolitik dienen können, werden häufig komplexe Methoden verwendet, um tatsächliche kausale Wirkungen von anderweitig verursachten Zusammenhängen zu unterscheiden. Der vorliegende Beitrag gibt einen nicht-technischen Überblick über Intuition und Anwendungsbeispiele des modernen wissenschaftlichen Instrumentariums zur Evaluierung kausaler Effekte. Die betrachteten ökonometrischen Methoden umfassen kontrolliert randomisierte Experimente, die Zufallsvergabe überzeichneter Programme, den Instrumentvariablen-Ansatz, den Regressions-Diskontinuitäten-Ansatz, den Differenzen-in-Differenzen-Ansatz sowie Panelmethoden mit fixen Effekten. Diese experimentellen und quasi-experimentellen Designs sollen der Wirtschaftspolitik helfen zu lernen, was funktioniert.

The recession that started in 2008 caused a sharp deterioration of the budget balance of Spain. This de-cline was not fully anticipated by the structural budget balance due to some methodology limitations. In this article, we calculate an alternative structural balance for Spain in the years prior to the subprime crisis that includes residential investment as an explanatory variable. This estimate shows that by 2004the Spanish fiscal situation was not as strong as presumed. This fragility was hidden by the extraordinary revenue from the real estate bubble and the construction boom.

This paper explores the relationship between gold prices and the US dollar/Turkish lira exchange rate between 1990–2011 by using cointegration and Granger causality analyses. The empirical findings indicate that there is a threshold cointegration relationship between the two variables. The threshold value obtained from the estimation of threshold vector error correction model equals −3.268. The Granger test indicates that there is evidence of a bi-directional causal relationship between gold prices and the exchange rate, except when the threshold parameter exceeds the threshold value in the exchange rate equation. According to these findings, gold price can be used as a hedge against the exchange rate. However, since this relationship disappears above the threshold value, gold is only a weak hedge against exchange rate fluctuations.

Small scale irrigation expansion has got vital role in assisting the development of sustainable agriculture in Ethiopia. And more number of small scale irrigation schemes were developed in the country including Gorogutu district of Oromia Region, considering the reality that irrigation is the obvious response to low agricultural productivity. The purpose of this study is therefore to assess the contribution of small-scale irrigation to household’s food security in Gorogutu district. Primary data were collected from 180 sample households selected from two PAs in the district, through random sampling technique based on probability proportional to size. The two PAs were selected considering the existence of small scale irrigation schemes, schemes years of operation and irrigation capacity. Binary Logit model was employed to examine the contribution of irrigation to household’s food security. The result of Binary Logit model indicates that use of irrigation water, family size in AE, off/non-farm income, total farm income, and livestock holding were found significantly influencing households food security. The marginal effect of the study showed that small-scale irrigation scheme utilization increases the probability of farm households to be food secure by 48%. The result is witnessed that irrigation has a great contribution to household’s food security and sustainable food security intervention must not exclude the improvement of production and productivity of agricultural sector through expansion of small-scale irrigation water use.

The macroeconomic indicators concern both the flows that are not fully or partially compensated over a time interval, which can be cumulated or integrated, and the stocks or funds identified in a particular moment. These indicators are addressed either as free real and nominal indicators, or as bound or non-autonomous financial indicators. Statistical and economic problems are methodologically distinguished by the need for connection (free real indicators are updated through the time bound indicators, while free nominal macroeconomic indicators are characterized by a certain autonomy in relation to real free indicators), and also by turning flows into stocks and stocks into flows. This paper details three distinct solutions for the transformation of stocks to flow, solutions of different degrees of generalization: economic, statistical and physical, and all of which are detailed below using debt and budget examples.

This paper uses multi-level factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework achieves dimension reduction and yet explicitly allows for heterogeneity between blocks. The model is estimated using a Markov chain Monte-Carlo algorithm that takes into account the hierarchical structure of the factors. We organize a panel of 447 series into blocks according to the timing of data releases and use a four-level model to study the dynamics of real activity at both the block and aggregate levels. While the effect of the economic downturn of 2007-09 is pervasive, growth cycles are synchronized only loosely across blocks. The state of the leading and the lagging sectors, as well as that of the overall economy, is monitored in a coherent framework.

We investigate the sustainability of Italy's public finances from 1862 to 2012 adopting a non-linear perspective. Specifically, we employ the smooth transition regression approach to explore the scope for non-linear fiscal adjustments of primary surpluses in response to the accumulation of debt. The empirical results show the occurrence of a significantly positive reaction of primary surpluses to debt when the debt-GDP ratio exceeded the trigger value of 110 percent. The after-threshold positive response implies that the path of Italy's fiscal policy is sufficiently consistent with the intertemporal budget constraint.

In recent work Im, Lee, and Enders (2006) use stationary instrumental variables to test for cointegrating relationships. The advantage of their approach is that the t-statistics are asymptotically standard normal and the familiar critical values of the normal distribution may be used to assess significance. Thus, the test avoids the nuisance parameter problem in single equation regressions for cointegration. Using an updated version of the data set developed by Taylor (2002), the ILE test is compared to three single equation alternatives in testing for purchasing power parity: An error correction model, autoregressive distributed lag model, and the Engle-Granger two step procedure. The regressions with instruments provide evidence supportive of PPP for some countries but the empirical results differ across tests and the choice of instrument can affect the results.

This study investigates and searches for a stable money demand function for Pakistan’s economy, where monetary aggregate is considered as the nominal anchor. The stability of the money demand has been the focus of numerous debates due to evolving financial innovations and regulations. Earlier studies in Pakistan on the subject provide conflicting explanations due to inadequate specification and imprecise estimation of money demand. However, this study finds that money demand in Pakistan is stable, if specified properly. Therefore, for developing countries, like Pakistan, targeting of monetary aggregates or responding to deviations from the desirable path is important for effective implementation and communication of monetary policy stance and it should remain, if not primary, an auxiliary target in the monetary policy framework.

Examining stationarity is of particular importance and represents the first step in empirical time-series research. Non-stationarity invalidates many of the results obtained from standard techniques and, therefore, requires special treatment. Because oil prices play an important role in affecting economic variables, this paper examines the stationarity of real oil prices (Brent, Dubai, WTI and the World) over the period 1973:2–2011:2. Real oil prices are expressed in the currencies of seven Asian countries (Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore and Thailand) and in the U.S. dollar. While using linear unit root tests without structural breaks shows no evidence of stationarity, allowing for breaks shows very limited evidence of stationarity. We argue that these results are attributed to the presence of nonlinearities in the behavior of oil prices. Testing for nonlinearity shows significant evidence of nonlinearity in all the cases with evidence of exponential smooth transition autoregression (ESTAR) nonlinearity-type in most cases. Applying unit root tests that account for two types of nonlinearities (smooth transition and nonlinear deterministic trends) reveals evidence of stationarity in all the cases.

The paper addresses a topical issue – how expansionary fiscal policy affects the debt to GDP ratio. It examines whether the projected future economic growth (stimulated by government spending) is sustained with the resulting national debt. It is discussedif government investment in infrastructure is an effective approach to boost the economy in times of economic downturn. The authors develop the debt to GDP ratio dynamics model and perform a series of simulations (based on US data) to forecast the evolution of the debt to GDP ratio over a 10-year horizon. It is shown that for the data characterizing the current state of the U.S. economy the government investment in infrastructure cannot decrease the debt to GDP ratio.

Under the hypotheses IA and IB, OLS estimators are both linear and stationary. For it to provide the same minimum variance of all linear and stationary estimators and to take part of BLUE, it is necessary that the classical assumptions IIB and IIC should be available. As in the case of two-variable regression, this means that the residual factors has to be homoschedastic and non-autocorrelated.

The aim of this paper is to investigate the presence of a causality relationship between the stock market and the foreign exchange market in the Czech Republic, Hungary, Poland, and Turkey. We first analyze the existence of structural breaks in the variance of stock and foreign exchange rate returns series. Then, we employ the causality-in-mean/variance test proposed by Hong (2001). Our empirical results suggest that stock markets Granger-cause foreign exchange markets for all the countries in both mean and variance. Therefore, it can be said that the stock market has an important role in the price discovery process for the foreign exchange market for the countries in question.

Multicollinearity implies near-linear dependence among regressors and is one of the diagnostics that harms enough the quality and the estimation of the regression models. Among the effects of multicollinearity can be mentioned that parameter estimates could lead to opposite signs or the variables turn out to having insignificant coefficients although it is known from theory or reality that the relationship exists. Also, when other variables are included or removed from the model this can affect the parameter estimates. Usually, multicollinearity is measured with the help of Variance Inflation Factor. A value greater than ten indicates severe multicollinearity in the model. Different approaches are known to reduce or eliminate multicollinearity effects but some of them are not always applicable due to data. The most used methods include addition of more data or elimination of the variable that is highly correlated with other independent variables or the use of the Ridge Regression. In addition to the well known and used models it is proposed here a new approach for the multicollinearity reduction. This method implies creating an index variable as a linear combination of the highly correlated ones. The index coefficients are selected under specific constraints imposed on the variables such that the new variable becomes highly correlated with the response variable but not with the independent ones. The best coefficients can be chosen out of the solution domain using an optimization program. In the new model, the highly correlated variables are replaced by the index one. The quality of the new model is improved by reducing or even eliminating the effects of multicollinearity. The regression model is expected to yield proper estimates. Also, VIF returns appropriate values, lower than ten. The method is exemplified on the BRD stock portfolio. Multicollinearity was eliminated, as showed by a value of one of the VIF and the model is expected to improve.

OLS is considered to be, by far, the most popular and well-known method for estimating parameters of multiple regression. In this case, however, it is important to underline that there is no warranty as to the fact that OLS estimators will be, in one way or another, some “perfect” estimators.

This present paper is analyzing the effect of trade openness and foreign direct investment (FDI) on industrial sector growth in Pakistan. This paper is examined that Pakistan’s industrial growth is affected by trade openness through a number of channels including monetary policy, fiscal policy, and Fdi. This study is employs Johansen and Juselius co-integration technique and Vector Error Correction Mechanism approach to estimate short run as well as long run relationship using annual time series data for the period 1960-2011. The study found that the relevant macro economic indicators Fdi and Real Gdp have positive and significant long run relationship with industrial sector growth while Trade openness and Inflation have negative long-run relationship with industrial sector growth also Real effective exchange rate have statistically insignificant results in long-run, on the other hand in short run lagged value of own industrial sector, Fdi, Reer, Real GDP have positive and significant impact on industrial sector growth. While inflation and trade openness shows insignificant relationship and Ec (-1) confirms long-run relationship among all independent variables.

The theory says that if stocks provide an effective hedge against inflation then the effect of expected inflation should be compensated in the form of nominal stock return. As Fisher Hypothesis (1930) concluded that nominal expected return on a security is a function of expected inflation rate as well as expected real interest rate. Bodie (1976) worked on Fisher Hypothesis and found that actual nominal return depends on expected and unexpected inflation rates and also it depends on expected and unexpected nominal returns. According to Geske and Roll (1983) a positive relationship exists between stock returns and inflation, based on the assumption that securities represent claims on real assets. When there is an increase in rate of inflation, it is expected that prices of real assets will also rise, thereby improving the value of securities representing a claim on such real assets. We found that various studies in this area reported against the hypothesis, showing a negative relationship between the two. However, certain other studies support the theory asserting that the relationship existing between stock returns and inflation is positive. While the negative relationship between inflation and stock return is against the theory, negative results have led to formation of hypothesis such as tax augmented hypothesis. The tax augmented hypothesis states that when we deduct tax from the stock returns, their relationship with inflation tends to get negative as the quantum and rate of taxes also rise along with inflation. This hypothesis also opines that initial researcher did not consider the tax impact when they were empirically testing the relationship between stock returns and inflation.

While many commentators perceive unemployment to be a key risk factor for intimate partner violence, the empirical evidence remains limited. We combine individual-level data from the British Crime Survey (BCS) with local labor market data to estimate the effects of total and gender-specific unemployment rates on domestic violence. The analysis uses the substantial variation in the increase in unemployment across areas, gender, and age-groups associated with the onset of the latest recession. Our main specification links a woman's risk of being abused to the unemployment rate among females and males in her local area and age group. Our results suggest that male and female unemployment have opposite-signed effects on domestic violence: while female unemployment increases the risk abuse, unemployment among males has the opposite effect. The result is shown to be robust to the inclusion of a wide set of control and also remains when we instrument for male and female unemployment using shift-share indices of labor demand. We argue that our findings are consistent with a theory of domestic violence in which (i) marriage provides insurance against employment risk through the pooling of resources, and (ii) a woman does not know the violent predisposition of her partner but infers it from his behavior. When the male partner face a high risk of unemployment, a potentially abusive husband strategically conceals his type as he has an economic incentive to avoid divorce and the associated loss of spousal insurance. However, when the female spouse faces a high risk of unemployment, her expected financial dependency on her partner prompts a husband with violent predisposition to reveal his abusive nature.

During the recent years, researchers as well as policy makers have been increasingly interested in impact evaluation of development programs. A large number of impact evaluations have been developed and applied to measure the impact of programs. Different impact evaluation methods rely on different identification assumptions. This paper presents an overview of several widely-used methods in program impact evaluation. In addition to a randomization-based method, these methods are categorized into: (i) methods assuming “selection on observable” and (ii) methods assuming “selection on unobservable”. The paper discusses each method under identification assumptions and estimation strategy. Identification assumptions are presented in a unified framework of counterfactual and two-equation model.Keywords: Program impact evaluation, treatment effect, counterfactual, potential outcomesJEL classification:C40, H43, J68.

A model with proportional errors in variables arising naturally in microeconomics is considered. Unlike the classical additive errors case, all OLS parameter estimates exhibit attenuation bias that does not depend on the limiting distribution of the data. The distribution of OLS estimators is developed. With no intercept, a simple correction of OLS based on mean predictions is identified that is consistent and asymptotically normal. With an intercept, a readily available additional moment based on sample data identifies the parameters. In neither case are additional restrictions or use of extra-sample data as instruments required as for common errors-in-variables methods.

The individual consumer of alcohol, often the household head, loses part of his income to buy alcohol. Excessive consumption of alcohol causes social costs (support costs of illness, family trauma, car accident, job loss and productivity etc.). Its effects on the health of the individual drinker are asymptomatic. If it is the case of a disease of alcoholism, the household must bear the costs of care, and those whose low-income or average income is below the permanent poverty, are confronted with a financial difficulty, drawing their savings and even selling their property to address this shortfall. The accumulation of costs caused by alcohol consumption is then a catastrophic expense for the household. The aim of the study is to show to what point we can calculate the risk of household poverty with an alcoholic individual head of household between the two periods: "disease free" and "appearance of the disease of alcoholism" Having obtained the value of the poverty line, a mathematical modeling of the expense of alcohol was made to derive an orientation axis to minimize the risk of poverty.

This paper develops a tractable dynamic microeconomic model of migration decisions that is aggregated to describe the behavior of interregional migration. Our structural approach allows us to deal with dynamic self-selection problems that arise from the endogeneity of location choice and the persistency of migration incentives. Keeping track of the distribution of migration incentives over time has important consequences for the econometrical treatment, because the dynamics of this distribution influences the estimation of structural parameters, such as migration costs. For US interstate migration, we obtain a cost estimate of less than one-half of an average annual household income. This is substantially smaller than the migration costs estimated by previous studies. We attribute this difference to the treatment of the dynamic self-selection problem.

Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y . This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person¡¯s wage, the unobserved D* indicates if the person has been to college, and the observed D indicates whether the individual claims to have been to college. This paper then identifies and estimates the difference in average wages between those who falsely claim college experience versus those who tell the truth about not having college. We estimate this average effect of lying to be about 6% to 20%. Nonparametric identification without observing D* is obtained either by observing a variable V that is roughly analogous to an instrument for ordinary measurement error, or by imposing restrictions on model error moments.

Real convergence of EU economies can be approached from the perspective of close relations between the state of homogeneity and the existence of conditions that can facilitate it. In this paper we test the hypothesis of beta convergence at national level for the group formed by all 27 EU member states (EU-27), for one of the old Member States (founding members and countries that joined in the first three waves of EU enlargement) (EU-15) and one of the new Member States (EU-10+2) (countries that joined in the last two waves of EU enlargement) and also at regional level for all 271 NUTS 2 regions. For reasons of comparison we will use the same indicator GDP per capita at purchasing power standards (PPS) for analysis of both levels. Given the availability of statistical information, we quantified applying the regression model, the marginal effect from GDP per capita growth caused by the change of condition expressed by the initial development stage.

The recent trend of globalization has given rise to a new paradigm in international economics, i.e. the simultaneous exports and imports of a product within country or a particular industry called intra-industry trade (IIT) or two-way trade. This study examines country-levels determinants of intra-industry trade, in U.S. trade. The manuscript applies a static and dynamic panel data approach. In contrast to previous studies, this paper used a dynamic panel data to solve the problems of serial correlation and endogeneity. The results indicate that IIT occurs more frequently among countries that are similar in terms of factor endowments. We also introduce economic dimension; this proxy confirms the positive effect of IIT. Our results also confirm the hypothesis that trade increases if the transportation costs decrease.

The purpose of this paper was to realize a multivariate analysis of the monthly unemployment rate in the county of Constanta using the following variables: the average net wage (SAL), the number of the employees (EMPL), the consumption price index (IPC) for the January 2000- march 2012 period. This analysis is based on the correlation study that can be established as a consequence of applying the parametric correlation methods between the mentioned indicator and the influential factors.

This study examines the determinants of intra-industry trade (IIT) between Pakistan and trade patterns in the period 1980-2006, using a static and dynamic panel data approach. In the recent years, the government of Pakistan had realized factors to liberalize the international trade. The literature of international economics demonstrates that this condition (trade liberalization) induces the IIT. The case study for Pakistan has been negligence in the economic literature. This study uses country-specific characteristics as explanatory variables. This study utilizes country-specific characteristics as explanatory variables. The empirical evidence indicates that IIT is a negative function of the difference in GDP per capita between Pakistan and her trading partners. Furthermore, econometric results point out that trading is influenced by the similar demand. We have also introduced an economic dimension; this proxy confirms the positive effects of IIT. Our findings reveal the importance of scales economies and the variety of differentiated products. The study supports to accept the hypothesis that trading increases if the transportation costs decrease.

The purpose of this research was to identify several features of the unemployment phenomenon in the SE region of Romania, using several of the most significant indicators highlighting the main correlations between specific labour market indicators and an indicator by which we can assess the economic development degree of a country. The resulted regression equations, tested from the point of view of their significance, allow, on the one hand, the assessment of the existing situation and, on the other hand, the performance of the forecasting calculations required to develop different scenarios and strategies for attracting investments and EU funds in order to reduce the number of the unemployed and to absorb higher education graduates on the labour market.

The current financial crisis generated a large debate for the degree to which the mathematical models are relevant for decision making in business and macroeconomic analysis. Instruments like Value-at-Risk, Copula functions and regressions were almost ”negotiated” in the non-specialized literature. The use of the mathematical tools in the economics profession and research probably started with the creation of the Econometrics Society in the 1930s and the foundation of the journal Econometrica, which, according to ISI Thomson Relative Influence Score, is the most prestigeous journal in the field of Applied Mathematics. This paper takes into account the ideas of normal distributions and the concepts of regression and factor analysis to present the way in which these mathematical models succeeded to create new ways of development in the field of economics.

In Romania approximately two thirds of the national production is generated by the private sector of the economy, which is still relatively a low value compared to the weight registered in the developed countries. The economic crisis has also affected the private enterprise sector. Some major features: the decrease of the new enterprise foundation ratio, the growth of business liquidation ratio. This process was rather asynchronous compared with that of the developed European Union countries. Based on some data sets, this article operates an econometric modeling of the newly created enterprises’ impact on the dynamic of national production, as measured by GDP.

Each year in preparation of annual financial statements must be evaluated the entity’s assets to be presented, so that these assets to be recorded in the financial statements at fair value need regular revaluation. Revaluations should be made with sufficient regularity so that the accounting value to does not differ substantially from that which would be determined using fair value at balance sheet date, so is guarateed the true and fair view of the financial statements. The study contains an analysis of the selected sample of 57 entities that responded to the questionnaire sent, with regard to: revaluation of assets of the entity, the reason of revaluation and the notion of true and fair view.

This paper aims to accurately characterize the dynamics of the structural indicators of the assets in the credit institutions operating in Romania through an empirical mathematical model of dual function:regulation and control. The model can be used to predict the future evolution of the economic processes involved, or to study how to act upon them (management) in case of changes in the environment around them (e.g. the impact of reducing the minimum compulsory reserve requirements on credit etc.).

Theory provides many explanations about the influence of electoral rules on politicians’ equilibrium behavior. With a few exceptions, all models agree that majoritarian elections are associated with more targeted redistribution and lower politicians’ rents than proportional representation. To sidestep the identification problems of previous empirical studies based on country-level data, we test these hypotheses using micro data for the mixed-member Italian House of Representatives. In particular, we address the nonrandom selection into different electoral systems by exploiting a particular feature of the Italian two-tier elections from 1994 to 2006: candidates could run for both the majoritarian and the proportional tier, but if they won in both tiers they had to accept the majoritarian seat. Focusing on elections decided by a narrow margin allows us to generate quasi-experimental estimates of the impact of the electoral rule. The main results confirm theoretical predictions, as majoritarian representatives put forward a higher proportion of bills targeted at local areas and show lower absenteeism rates than their proportional colleagues.

Ethnic differences influence entrepreneurship development as well as its success or failure. In Nigeria, ethnicity is one of the keys to understanding pluralistic nature of our society. One thing to note is that the various ethnic groups in Nigeria have achieved varying levels of success in their entrepreneurship development and its subsequent success. Thus, this paper tried to evaluate the disparity that seems to exist among indigenous ethnic groups and entrepreneurial success in Nigeria using and OLS estimation of primary sourced data. The results from the study suggest that though membership of an ethnic group is an important factor in achieving entrepreneurial success in Nigeria, there are some other factors that influence entrepreneurial success in Nigeria. Among these factors are: access to financial capital, education (including vocational training) at start up, and prior business experience.