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Econometric Issues In The Analysis Of Regressions With Generalized Regressors
... The estimated coefficients of Equation (17) and their standard errors are presented in Table 6. Adhering to methods from Pagan (1984) and Shanken (1992), we also adjust the standard errors for our estimated regressors. Table 6 corroborates the suggestion from Panel A of Figure 1: the predicted entropy premium is most negative in times of high dispersion, high average, high skewness in predicted entropy, and when entropy is predictable. ...
... Overall, while the risk coefficients in most models of Table 7 are smaller compared to our baseline portfolio results, the expected IE demonstrates considerable explanatory power in (17). To ensure accuracy, we have adjusted the standard errors of this model to consider the generated regressors as per Pagan (1984) and Shanken (1992), along with the time-series correlation methods outlined by Newey and West (1987). The symbol *** indicates that the results are statistically significant at the 10% level Source(s): Created by the author Table 6. ...
Purpose
We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.
Design/methodology/approach
We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.
Findings
We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.
Originality/value
We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.
... There are some theoretical and empirical investigations on the statistical power of the RESET test, in particular, and variable addition tests in general. Thursby and Schmith (1977) examine the power using fixed alternative hypothesis, whereas Pagan (1982) ...
... Source: Data entries are probabilities of rejecting the null hypothesis. The RESET test is replicated 5000 times for the specification (6) and (7). The size of the test is α=0.025. ...
The present paper aims to demonstrate that the Ramsey’s Regression Specification Error Term Test (RESET) is very sensitive to the degree of nonlinearity between the variables of the under-specification functional form. This widely used test, for testing the functional specification of a model, is based on the notion that if nonlinear combinations of the explanatory variables have any power in explaining the predictor, the model is mis-specified and the data generating mechanism might be approximated by a nonlinear functional form. Using Monte Carlo techniques, we find that the power of the Ramsey’s RESET test is highly influenced and related with the degree of nonlinearity between the dependent and the independent variables of the under-specification functional form.
... Eq. (14) includes a pooled OLS regression of leverage changes on the product of Dist i;t;j and liquidity and control variables with bootstrapped standard errors to account for the generated regressors (Çolak et al., 2018;Faulkender et al., 2012;Pagan, 1984). Table 3 reports the results. ...
Purpose
We explore the impact of equity liquidity on a firm’s dynamic leverage adjustments and the moderating impacts of leverage deviation and target instability on the link between equity liquidity and dynamic leverage in the UK market.
Design/methodology/approach
In applying the two-step system GMM, we estimate our model by exploring suitable instruments for the dynamic variable(s), i.e. lagged values of the dynamic term(s).
Findings
Our analyses document that a firm’s equity liquidity has a positive impact on the speed of adjustment (SOA) of its leverage ratio back to the target ratio in the UK market. We also demonstrate that the positive relationship between liquidity and SOA is more pronounced for firms whose current position is relatively close to their target leverage ratio and whose target ratio is relatively stable.
Practical implications
This study provides important implications for both firms’ managers and investors. Particularly, firms’ managers who wish to increase the leverage SOA to enhance firms’ value need to give great attention to their equity liquidity. Investors who want to evaluate firms’ performance could also consider their equity liquidity and leverage SOA.
Originality/value
We are the first to enrich the literature on leverage adjustments by identifying equity liquidity as a new determinant of SOA in a single developed country with many differences in the structure and development of capital markets, ownership concentration and institutional characteristics. We also provide new empirical evidence of the joint effect of equity liquidity, leverage deviation and target instability on leverage SOA.
... Eq. (5) includes a pooled OLS regression of leverage changes on the product of Dist ijt and the main variable effecting leverage SOA (i.e., carbon risk and earnings yield) and control variables with bootstrapped standard errors to account for the generated regressors (Faulkender et al., 2012;Pagan, 1984). ...
... Also whilst Ng (2006, 2008b) and Bai and Ng (2008a) show in linear models that the factor estimates can be treated as known if √ T∕N → 0 , as in our case, there may be a question whether generated regressors drive our results. We go with the grain of Pagan (1984) and use GMM to circumnavigate this potential issue to obtain consistent estimates of the relationship between climate risk and macroeconomic activity. We find evidence of a stronger and more deleterious impact upon macroeconomic activity from the global climate risk factor, relative to idiosyncratic results, using dynamic panel systems GMM, including with robust standard errors. ...
This paper examines the impact of climate risk on macroeconomic activity for thirty countries using over a century of panel time series data. The key innovation of our paper is to use a factor stochastic volatility approach to decompose climate change into global and country-specific climate risk and to consider their distinct impact upon macroeconomic activity. To allow for country heterogeneity, we also differentiate the impact of climate risk upon advanced and emerging economies. While the existing literature has focused on country based climate risk shocks, our results suggest idiosyncratic or country-specific climate risk shocks are relatively unimportant. Global climate risk, on the other hand, has a negative and relatively more important impact on macroeconomic activity. In particular, we find that both advanced and emerging countries are adversely impacted by global climate risk shocks.
... This nonlinear model is much more involved than the generalized linear model (15), which produces the same α. Generalized linear model in (9) is a model with an omitted variable [34], whereas the proposed model (15) is a generated regressor model [35]. What is missing in (9) is a variable responsible for the relationship between the inclination to participate and the response, when this exists. ...
... In the TSRA method, the main variables used in the second stage are those that have been generated in the first stage. It is therefore important to adjust the standard errors to account for the sampling variance of generated variables constructed in the first stage (Pagan 1984). Thus, as well as reporting the usual robust standard errors clustered at the parental level, adjusted standard errors calculated using a bootstrap procedure are reported. ...
Using a new dataset combining the British Household Panel Survey (BHPS) and Understanding Society (UKHLS), this paper examines the current state of intergenerational income mobility in the UK. This extends previous evidence in several directions, with a focus on younger cohorts of individuals born between 1973 and 1992. I find evidence of considerable intergenerational persistence in the transmission of resources at the household level with an intergenerational elasticity of 0.26 and a rank coefficient of 0.30. This picture of mobility remains at the individual level and under a range of robustness tests that address traditional methodological concerns. While mobility is relatively low at the national level, I find meaningful differences in income mobility rates across the country. More generally, regions with lower income in the North of England display substantially lower levels of both relative and absolute income mobility than regions in the South.
... We estimate our internally-consistent simultaneous equations model by full information maximum likelihood, avoiding Pagan's (1984) generated regressor problems. We associate the oil price change VAR residual with exogenous oil price shocks, use the conditional standard deviation of the forecast error for the change in the real oil price as a measure of uncertainty about the impending real price of oil, and find that oil price uncertainty has had a negative and statistically significant effect on real GDP growth. ...
This paper investigates the relationship between the price of oil and real output in the United States in the context of a Markov regime switching, identified, structural GARCH-in-Mean VAR model with copulas. We use the copula method to investigate the nonlinear dependence structure, as well as (upper and lower) tail dependence, between the price of oil and real output growth, and Markov regime switching to account for changing oil price dynamics over the sample period. We find an asymmetric negative dependence structure between oil price and output growth shocks and that oil price uncertainty has a negative and statistically significant effect on real output growth.
... This two-stage approach is an example of statistical inference with generated regressors (Pagan, 1984;Oxley and McAleer, 1993). It has seen growing adoption in social sciences, partly due to impressive advances in machine learning techniques to efficiently extract useful information from large amounts of both structured and unstructured data. ...
Despite increasing popularity in empirical studies, the integration of machine learning generated variables into regression models for statistical inference suffers from the measurement error problem, which can bias estimation and threaten the validity of inferences. In this paper, we develop a novel approach to alleviate associated estimation biases. Our proposed approach, EnsembleIV, creates valid and strong instrumental variables from weak learners in an ensemble model, and uses them to obtain consistent estimates that are robust against the measurement error problem. Our empirical evaluations, using both synthetic and real-world datasets, show that EnsembleIV can effectively reduce estimation biases across several common regression specifications, and can be combined with modern deep learning techniques when dealing with unstructured data.
... The major advantage of the realized volatility is that it is model-free, and hence void of measurement or specification errors. By inference, it does not suffer the generated regressor problem associated with two-step estimation procedures (Pagan 1984). And other control variables such as real gross domestic product (RGDP), real effective exchange rate, and inflation (first difference of consumer price index in our case) are included in the study. ...
There is no yet clear theoretical and empirical consensus on the relationship between exchange rate uncertainty and domestic investment. The main purpose of this study, therefore, is to examine the effect of real effective exchange rate uncertainty on domestic investment for the Ethiopian economy over the sample period 1992Q1- 2016Q1. To address this objective, Jordà’s (2005) local projection method is employed and generalized impulse response functions are generated in this study. The impulse response functions exhibit that one standard deviation shock in exchange rate uncertainty stimulates domestic investment for the Ethiopian economy. In response to one standard deviation shock in exchange rate uncertainty, domestic investment increases to around 4 percent at the second quarter. This may indicate the existence of risk neutral or insensitive domestic investors to exchange rate uncertainty in Ethiopia. As to the effects of other control variables, domestic investment also increases in response to real income and real effective exchange rate shocks. The effect of inflation shock on domestic investment is positive and statistically significant up to the eighth quarter, and negative and significant afterwards.
... Inclusion of estimated quantities in regression models may affect the asymptotic distribution of the parameter estimates, see Pagan (1984). This observation is essential in our context, characterized by a quantile factor model with estimated factors. ...
This paper proposes a functional coefficient quantile regression model with heterogeneous and time-varying regression coefficients and factor loadings. Estimation of the model coefficients is done in two stages. First, we estimate the unobserved common factors from a linear factor model with exogenous covariates. Second, we plug-in an affine transformation of the estimated common factors to obtain the functional coefficient quantile regression model. The quantile parameter estimators are consistent and asymptotically normal. The application of this model to the quantile process of a cross-section of U.S. firms’ excess returns confirms the predictive ability of firm-specific covariates and the good performance of the local estimator of the heterogeneous and time-varying quantile coefficients.
Purpose
The purpose of this study is to evaluate the linkage between stock markets in Middle Eastern countries before and during the COVID-19 pandemic by using daily and monthly data sets for the period from 2011 to 2021.
Design/methodology/approach
The multivariate BEKK-GARCH model was computed to evaluate the existence of non-linear linkage among Middle Eastern stock markets. A correlation approach was used in this study to determine the type of linear connectivity between Middle Eastern stock markets. The study used monthly and daily data sets covering the years 2011 to 2021 to investigate the linkage between stock returns and the volatility spillover between the stock markets in Palestine, Jordan, Syria and Lebanon, both before and during COVID-19. To understand the types of relationships between markets before and during COVID-19, the daily data set was split into two periods.
Findings
Results from the pre-COVID-19 suggest that the Syria stock market is not related to any stock market in the Middle East markets; the Palestine and Lebanon stock markets exhibit a weak relationship, but Jordan and Palestine stock markets are strongly linked. Conversely, results from COVID-19 evince a very strong bidirectional volatility spillover between Middle East stock markets. Overall, the results indicate the existence of increased linkage during the COVID-19.
Research limitations/implications
The data collection on a daily and monthly basis, both before and during COVID-19, presents certain limitations for the paper. Another limitation is that the data cannot be generalized to all other Middle Eastern countries; rather, the conclusions drawn can only be applied to these four countries. This is especially true if the scholars collected most of the necessary data but were unable to obtain certain data for various reasons.
Practical implications
These findings have implications for risk management, market regulation and the growth of local stock markets. Facilitating the growth of smaller, more specialized markets to improve integration with other Middle Eastern markets is one of the goals of the domestic stock market development policy. To ensure financial stability, Middle Eastern stock market linking policies should consider spillover risk and take steps to minimize it. Enhancing the range of investment opportunities accessible to shareholders and functioning as confidential risk-sharing mechanisms to facilitate improved risk management in Middle Eastern stock markets will not only significantly influence the mobilization of private capital to promote investment and local economic growth but also lay groundwork for integrated market platforms.
Originality/value
This paper adds to the body of literature by demonstrating the nature of the connections between these small markets and the larger markets in the Middle East region. Information from the smaller markets provides institutional insights that enhance the body of existing research, guide the formulation of evidence-based policies and advance financial literacy in these markets. This study contributes by comparing data from different stock markets to better understand the type and strength of the link and relationship between Middle Eastern stock markets, as well as any underlying or reinforcing factors that might have contributed to the relationship and the specific types of links that these markets shared prior and during COVID-19.
We examine the persistence of teachers’ gender biases by following teachers over time in different classes. We find a very high correlation of gender biases for teachers across their classes. We find a substantial impact of gender bias on student performance in university admissions exams, choice of university field of study, and quality of the enrolled program. The effects on university choice outcomes are larger for girls, explaining some gender differences in STEM majors. Teachers with lower value-added are also more likely to be gender biased. (JEL I21, I23, J16, J24, J45)
This paper studies the asymptotic properties of endogeneity corrections based on nonlinear transformations without external instruments, which were originally proposed by Park and Gupta (2012) and have become popular in applied research. In contrast to the original copula-based estimator, our approach is based on a nonparametric control function and does not require a conformably specified copula. Moreover, we allow for exogenous regressors, which may be (linearly) correlated with the endogenous regressor(s). We establish consistency, asymptotic normality and validity of the bootstrap for the unknown model parameters. An empirical application on wage data of the US current population survey demonstrates the usefulness of the method.
Managers tend to issue equity when a firm is overvalued. Short selling is more frequent among overvalued firms. By conditioning short selling on overvaluation, we show that short selling increases leverage, lenghtens debt maturity, and speeds up adjustment to target leverage. The leverage increase is more pronounced in firms with independent boards and an increased likelihood of misvaluation, is driven by overvaluation relative to long‐run value, and occurs through lower equity issuance and higher long‐term debt issuance. Analyses using the exogenous shock to the short‐selling environment from the US Securities and Exchange's Reg SHO pilot program suggest these results are causal.
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This paper considers the problem of inferring the causal effect of a variable Z on a dependently censored survival time T. We allow for unobserved confounding variables, such that the error term of the regression model for T is dependent on the confounded variable Z. Moreover, T is subject to dependent censoring. This means that T is right censored by a censoring time C, which is dependent on T (even after conditioning out the effects of the measured covariates). A control function approach, relying on an instrumental variable, is leveraged to tackle the confounding issue. Further, it is assumed that T and C follow a joint regression model with bivariate Gaussian error terms and an unspecified covariance matrix, such that the dependent censoring can be handled in a flexible manner. Conditions under which the model is identifiable are given, a two-step estimation procedure is proposed, and it is shown that the resulting estimator is consistent and asymptotically normal. Simulations are used to confirm the validity and finite-sample performance of the estimation procedure. Finally, the proposed method is used to estimate the causal effect of job training programs on unemployment duration.
A procedure is outlined aiming at testing the bias due to omitted variables in vector autoregressions. The procedure consists first of filtering a vector of omitted variables and then testing the bias. The test does not rely on the availability of the omitted variables, and is based on a comparison between maximum-likelihood with Kalman filter vector autoregression and linear vector autoregression estimates. The empirical part considers two illustrative examples: a univariate regression analysis, based on the rational expectation-augmented Phillips curve; and a VAR with output, inflation and interest rates where a “price puzzle” arises.
Purpose
The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).
Design/methodology/approach
Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.
Findings
The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.
Originality/value
Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).
In the setting of a dynamic panel data framework, we investigate the international five‐factor Fama–French (2017) model augmented with traditional illiquidity factors (Amihud, Journal of Financial Markets, 2002, 5, 31–56; Amihud, Critical Finance Review, 2019, 8, 203–221; Pástor and Stambaugh, Journal of Political Economy, 2003, 111, 642–685; Pástor and Stambaugh, Critical Finance Review, 2019, 8, 277–299) to determine if any of these factors are priced. Since illiquidity measures are endogenous, we propose an algorithm that generates robust instruments which are combined with a GMM estimator to cope with both the endogeneity issues surrounding illiquidity and other eventual specification errors. In this dynamic framework, we generally find that the most significant factors correspond to market and size but illiquidity may matter depending on the level of the beta. We find that illiquidity has more impact on returns in expansion than in recession. However, the bid‐ask spread seems to behave differently from the other illiquidity measures.
Purpose
This paper aims to examine the effects of oil price uncertainty on corporate investment of Islamic stocks during the COVID-19 pandemic.
Design/methodology/approach
The study uses a panel data set that covers 398 listed Islamic stocks from seven major Asia Pacific countries over the period of five years from 2017 to 2021, yielding 1,990 observations. Specifically, this paper investigates the said association by combining the real options theory regarding investment and the panel data-based econometric method that captures the dynamic relationship, the generalized method of moments estimators.
Findings
The findings show that the relationship between the oil price volatility and corporate investment of Islamic stocks is significant and nonlinear in nature, suggesting the presence of both the growth options and the waiting options. Overall, the results reveal that corporate investment of Islamic stocks is hindered during the unprecedented corona crash, when oil price increases at exponential rates.
Practical implications
The findings suggest that considering the information caused by unprecedented events like the COVID-19 pandemic is crucial for investment decisions of Islamic stocks. Therefore, policymakers and regulators should incorporate the impact of oil price uncertainties caused by unprecedented events like the COVID-19 pandemic on firm’s investment expansion and diversification strategies.
Originality/value
To the best of the authors’ knowledge, this paper is the first to examine the relationship between the investment of Islamic stocks and the oil price uncertainty under compound options theory in top Asian oil-importing countries.
The small Indian mongoose (Urva auropunctata) is a rabies reservoir on several Caribbean Islands including Puerto Rico. In the continental United States, oral rabies vaccination (ORV) has been used to control and locally eliminate rabies viruses targeting meso-carnivores including raccoons (Procyon lotor), grey foxes (Urocyon cinereoargenteus), and coyotes (Canis latrans), and has more recently been proposed to mitigate and control mongoose rabies in Puerto Rico. A fundamental understanding of the population density of the target species is an important factor in planning bait application rates prior to ORV operations. In Puerto Rico, most ecological studies on mongooses have been restricted to the rainforest region in the northeastern portion of the island. We calculated population density estimates for mongooses at seven sites representing four habitat types in Puerto Rico. We marked 445 unique mongooses across 593 capture events during 12,530 trap days during 2016–2021. Mean (SE, 95% CI) population densities were greater in closed to open broadleaved evergreen forest habitat (0.79 ±0.13, 0.67–0.92 mongooses/ha) compared to grasslands (0.43 ± 0.10; 0.35–0.55 mongooses/ha), rainfed croplands (0.26 ±0.10, 0.18–0.38 mongooses/ha), and shrub/herbaceous habitat (0.19 ±0.05, 0.15–0.25 mongooses/ha). We did not detect seasonal variation in mongoose population density (0.48 [0.06; 0.35–0.62] and 0.39 [0.06; 0.27–0.50] mongooses/ha measured in the wet (May–November) and dry (December–April) seasons, respectively. Multiple ORV applications may be needed annually for adequate population immunity, particularly in habitats with high mongoose population densities and rapid population turnover.
This paper investigates the relationship between female CEOs and insolvency risk of US property‐casualty insurance companies. We show that female CEOs are associated with lower insurer insolvency propensity, higher z ‐score, and lower standard deviation of return on assets. These findings are robust to alternative econometric specifications to address potential endogeneity concerns and self‐selection issues, including propensity score matching, the instrumental variable approach, and the difference‐in‐difference approach. Furthermore, we find that the impact of female CEOs on insurer insolvency risk is moderated by firm capitalization, the presence of female directors, and political conservatism of insurers' home states.
In this paper we provide a general two‐step framework for linear projection estimators of impulse responses in structural vector autoregressions (SVARs). This framework is particularly useful for situations when structural shocks are identified from information outside the VAR (e.g. narrative shocks). We provide asymptotic results for statistical inference and discuss situations when standard inference is valid without adjustment for generated regressors, autocorrelated errors or non‐stationary variables. We illustrate how various popular SVAR models fit into our framework. Furthermore, we provide a local projection framework for invertible SVAR models that are estimated by instrumental variables (IV). This class of models results in a set of quadratic moment conditions used to obtain the asymptotic distribution of the estimator. Moreover, we analyse generalized least squares (GLS) versions of the projections to improve the efficiency of the projection estimators. We also compare the finite sample properties of various estimators in simulations. Two highlights of the Monte Carlo results are (i) for invertible VARs our two‐step IV projection estimator is more efficient compared to existing projection estimators and (ii) using the GLS projection variant with residual augmentation leads to substantial efficiency gains relative to standard OLS/IV projection estimators.
In response to a change in interest rates, younger firms not paying dividends adjust both their capital expenditure and borrowing significantly more than older firms paying dividends. The reason is that the debt of younger non-dividend payers is far more sensitive to fluctuations in collateral values, which are significantly affected by monetary policy. The results are robust to a wide range of possible confounding factors. Other channels, including movements in interest payments, product demand, profitability and mark-ups, are also significant but seem unlikely to explain the heterogeneity in the response of capital expenditure. Our findings suggest that these types of financial frictions play an important role in the transmission of monetary policy.
When conducting regression analysis, econometricians often face the situation where some relevant regressors are unavailable in the data set at hand. This article shows how to construct a new class of nonparametric proxies by combining the original data set with one containing the missing regressors. Imputation of the missing values is done using a nonstandard kernel adapted to mixed data. We derive the asymptotic distribution of the resulting semiparametric two-sample estimator of the parameters of interest and show, using Monte Carlo simulations, that it dominates the solutions involving instrumental variables and other parametric alternatives. An application to the PSID and NLS data illustrates the importance of our estimation approach for empirical research.
This research outlines and tests two corporate social responsibility (CSR) views of the corporate leverage speed of adjustment (SOA). The first view (stakeholder value maximization) indicates that socially responsible firms commit to ethical behavior and provide reliable financial information, which is advantageous to access external financing, and thus these firms tend to gain faster leverage adjustments. The second view (overinvestment) predicts that if managers over-invest in CSR due to agency problems, CSR may raise external financing's concerns and is related to slower leverage adjustments. Our findings strongly support the first view. We further find that the positive effect of CSR on SOA is more pronounced for firms with high information asymmetry, high financial constraints, and high adjustment costs. Taken together, this study generates important insight that CSR can reduce leverage adjustment costs stemming from information asymmetry, thereby leading to faster leverage SOA.
Whereas there is substantial evidence that economic freedom generates positive growth effects, much less is known about how social values impact the institutional framework underlying economic freedom. We address this gap in the literature, using panel data for a heterogeneous group of countries for the period 1980–2010 to examine whether post materialism influences the growth effect of economic freedom. Using instrumental variable estimation techniques within a three stages least square framework, we find that Fraser's economic freedom index and several of its components generate positive direct growth effects. Post materialism generates a negative direct growth effect. We also identify a positive indirect effect from post materialism that runs via economic freedom and its underlying components onto economic growth. These findings indicate that post materialism influences the institutional framework underlying economic freedom and that economic freedom acts as a transmission channel of economic effects of social values.
The debate on the need for Sub-Saharan African (SSA) countries to increase female participation in the economic sector has intensified the coming into force of the African Continental Free Trade Area (AfCFTA) and good governance. This study investigates the joint effects of governance (comprising of political, economic and institutional governance) and trade openness on female economic participation in SSA. The study employs panel data of 42 countries in SSA for the period 1996–2020. The empirical strategy is the dynamic System Generalized Method of Moments (SGMM) estimation technique. The findings reveal that the single effect of trade openness on female economic participation is necessary but not sufficient. Hence, complementing trade openness with good governance further enhances female economic participation in SSA. In general, the joint effect of trade openness and good governance should be a concern for policy makers to promote female economic inclusion.
The classical Lindeberg-Feller CLT for sums of independent random variables (rv's) provides more than the convergence in distribution of the sum to a normal law. The independence of summands also guarantees the weak convergence of all finite dimensional distributions of an a.e. sample continuous stochastic process (suitably defined in terms of the partial sums) to those of a Gaussian process with independent increments, namely, the Wiener process. Moreover, the distributions of said process converge weakly to Wiener measure on $C\lbrack 0, 1\rbrack$, the latter result being known as an invariance principle, or functional CLT, an idea originating with Erdos and Kac [10] and Donsker [5], then developed by Billingsley, Prohorov, Skorohod and others. The present work contains an invariance principle for a certain class of martingales, under a martingale version of the classical Lindeberg condition. In the case of sums of independent rv's, our results reduce to the conventional invariance principle (see, for example, Parthasarathy [16]) in the setting of the classical Lindeberg-Feller CLT. Theorem 1 contains a type of martingale characteristic function convergence which is strictly analogous to the classical CLT, while Theorem 2 provides weak convergence of finite dimensional distributions to those of a Wiener process, followed by (Theorem 3) the weak convergence of corresponding induced measures on $C\lbrack 0, 1\rbrack$ to Wiener measure, thus entailing an invariance principle for martingales. Notation and results are listed in Section 2. Section 3 defines the Lindeberg condition for martingales and gives it several equivalent forms. Sections 4 and 5 contain the proofs of Theorems 1 and 2, respectively, while Theorem 3 is proved in Section 6 by use of a martingale inequality derived from an upcrossing inequality of Doob [7]. Section 7 contains brief remarks. Among the large literature on CLT's for sums of dependent rv's, mention of a martingale CLT is first made by Levy [12], [13], followed by Doob [6] page 383. Billingsley [2] and Ibragimov [11] gave a version for stationary ergodic martingales, and Csorgo [4] considered related problems. The author also knows of Dvoretsky [8]. Invariance principles for various dependent rv's were found by Billingsley [1], and in [3] for stationary ergodic martingales, the latter result being given by Rosen [17] for bounded summands. The present Theorem 3 relaxes the stationarity and ergodicity requirements of Billingsley's Theorem (23.1) of [3]. Since preparing the original version of this paper, the author's attention has been drawn to Dvoretsky [9], which announces a result strongly resembling the present Theorem 2, and to the CLT [14] and invariance principle [15] for reversed martingales, due to Lyones. The methods of Section 5 are owed to Billingsley [2] (who in turn acknowledges a "debt to Levy") and to ideas given by Dvoretsky [8]. Finally, I wish to thank Dr. C. C. Heyde, for making a vital remark, and Mr. David Scott, for helpful criticism.
A price dispersion equation is tested with data from the German hyper-inflation. The equation is derived from a version of Lucas' (1973) and Barro's (1976) partial information-localized market models. In this extension, different excess demand elasticities across commodities imply a testable dispersion equation, in which the explanatory variable is the magnitude of the unperceived money growth. The testing of this hypothesis requires two preliminary steps. First, a price dispersion series is computed using an interesting set of data. It consists of monthly average wholesale prices of 68 commodities ranging from foods to metals, for the period of January, 1921 to July, 1923. The next step is the delicate one of measuring unperceived money growth. This estimation implies the postulation of an available information set and also a function relating the variables in this set to money creation. The function used was based on considerations related to government demand for revenue. The model receives support from the empirical analysis although it is evident that unincluded variables have important effects on price dispersion.
This paper discusses ongoing research on the relation of money to economic activity in the post-World War I1 United States. As in previous work, the stress is on the distinction between anticipated and unanticipated movements of money. Part I deals with annual data. Aside from updating and refinements of earlier analysis, the principal new results concern joint, cross-equation estimation and testing of the money growth, unemployment, output and price level equations. The present findings raise some doubts about the specification of the price equation, although the other relations receive further statistical support. Part I1 applies the analysis to quarterly data. Despite the necessity to deal with pronounced serial correlation of residuals in the equations for unemployment, output and the price level, the main results are consistent with those obtained from annual data. Further, the quarterly estimates allow a detailed description of the lagged response of unemployment and output to money shocks. The estimates reveal some lack of robustness in the price equation, which again suggests some misspecification of this relation.
S ummary
The asymptotic properties of m.l.e. are discussed for generally dependent observations. Conditions are derived for weak consistency and asymptotic Normality of the estimates. We further consider the case where some of the parameters are “transient” in the sense that the accumulated information on them from the sample does not increase indefinitely; then the interest lies in estimating the other parameters consistently. Examples are given, and the work is related to that of Neyman and Scott (1948).
Empirical tests of the neutrality of money growth found in recent literature are tests of the joint hypothesis of rational expectations and structural neutrality. Although tests of this joint hypothesis are informative, it is also important to gain information on the accuracy of its constituents. This paper presents the application of a methodology capable of providing information on the empirical validity of the rational expectations, structural neutrality, and joint hypotheses. Tests of these hypotheses are performed on the basis of FIML estimation of an extended version of a model recently presented by Robert Barro, using U.S. data for 1946–1973.
General results are given in this paper which allow the development of a theory of estimation and inference for situations in which the model of a data-generating process has been misspecified. Observations may come from time-series, cross-section, panel, or experimental data. The nonlinear regression model is examined in some detail. Conditions are provided which ensure the consistency and asymptotic normality of the least-squares estimator with respect to the parameter vector of a weighted least-squares approximation to the underlying data-generating process. A specification-robust estimator of the asymptotic covariance matrix is given, allowing a proper treatment of inference in potentially misspecified models. The properties of the approximation and the covariance estimator are exploited to yield new tests for model specification.
The policy implications of combining rational expectations with the natural rate of unemployment hypothesis are reviewed. A monetary policy feedback rule is estimated on Canadian data for the period 1927–1972. The residuals from the regression serve as the unanticipated components of monetary policy while predicted values serve as expected monetary growth. An unemployment equation is then developed in which the unemployment rate is allowed to be influenced by expected and unexpected monetary policy and fiscal and foreign spending. The evidence confirms the hypothesis that it is unanticipated monetary policy that affects unemployment and that anticipated monetary growth plays no significant role.
This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formal model of the structure of the heteroskedasticity. By comparing the elements of the new estimator to those of the usual covariance estimator, one obtains a direct test for heteroskedasticity, since in the absence of heteroskedasticity, the two estimators will be approximately equal, but will generally diverge otherwise. The test has an appealing least squares interpretation.
Recent theorizing with business cycle models which incorporate features of the Friedman-Phelps natural rate model along with rational expectations lead to the following policy conclusions. Anticipated changes in aggregate demand policy will have already been taken into account in economic agents behavior and will thus evoke no further output or employment response. Therefore, deterministic feedback policy rules will have no impact on output fluctuations in the economy. These policy implications of what Modigliani has dubbed the Macro Rational Expectations (MRE) hypothesis are of such importance that a wide range of empirical research is needed for its verification or refutation. Recent empirical work has tested the "neutrality" implication of the MRE hypothesis that anticipated monetary policy does not affect output or unemployment. Although this empirical work has frequently been favorable to the MRE hypothesis, it suffers from several deficiencies that create suspicion about the robustness of the results. This paper is an attempt to conduct an econometric investigation of the implications of the MRE hypothesis which does not suffer from these deficiencies. The results here strongly reject the neutrality implications of the MRE hypothesis: unanticipated movements in monetary policy are not found to have a larger impact on output and unemployment than anticipated movements. This evidence casts doubt on previous evidence that is cited as supporting the view that only unanticipated monetary policy is relevant to the business cycle.
This paper examines the hypothesis that the expected rate of return to speculation in the forward foreign exchange market is zero; that is, the logarithm of the forward exchange rate is the market's conditional expectation of the logarithm of the future spot rate. A new computationally tractable econometric methodology for examining restrictions on a k-step-ahead forecasting equation is employed. Using data sampled more finely than the forecast interval, we are able to reject the simple market efficiency hypothesis for exchange rates from the 1970s and the 1920s. For the modern experience, the tests are also inconsistent with several alternative hypotheses which typically characterize the relationship between spot and forward exchange rates.
This paper investigates the importance of uncertainty regarding the rate of rice change as an argument in the long-run money demand function. Increased inflation uncertainty is assumed to lower the stream of monetary services yielded by a given level of real cash balances. The effects on money demand of such changes in the "quality" of money are, in general, theoretically indeterminate. If it is assumed, however, that the monetary service flow is proportional to the real money stock and that the demand for money is interest inelastic, then the predicted relationship between price uncertainty and money demand is unambiguously positive. The empirical findings of this paper, where price uncertainty is operationally measured by the variability of the rate of price change, strongly confirm this positive relationship. These results have important implications for the theory of inflation, the optimum quantity of money, and the potential government tax revenue from money creation.
In the past several decades, professional views on the relation between inflation and unemployment have gone through two stages and are now entering a third. The first was the acceptance of a stable trade-off (a stable Phillips curve). The second was the introduction of inflation expectations, as a variable shifting the short-run Phillips curve, and of the natural rate of unemployment, as determining the location of a vertical long-run Phillips curve. The third is occasioned by the empirical phenomenon of an apparent positive relation between inflation and unemployment. The paper explores the possibility that this relation may be more than coincidental.
A statistical definition of the natural unemployment rate hypothesis is advanced and tested. A particular illustrative structural macroeconomic model satisfying the definition is set forth and estimated. The model has "classical" policy implications, implying a number of neutrality propositions asserting the invariance of the conditional means of real variables with respect to the feedback rule for the money supply. The aim is to test how emphatically the data reject a model incorporating rather severe classical hypotheses.
This paper reports on an empirical study of the effects of interest rates and inflation on aggregate consumption in the United States. Empirical evidence, based on quarterly U.S. data from the postwar period, is first presented in support of the hypothesis that the real rate of interest varies inversely with the rate of inflation, at least in the short run. Regression estimates of an aggregate consumption function for the United States, also based on quarterly data from the postwar period, are then presented. These estimates indicate that the propensity to consume varies inversely with interest rates and directly with the rate of inflation.
A rational expectations model is developed in which prices are fixed during a period. The implications of this model are that output fluctuations are correlated with unanticipated aggregate demand but not with unanticipated inflation. Empirical tests of the model indicate that the persistence of business cycles cannot be explained solely by unanticipated aggregate demand.
Corruption in the public sector erodes tax compliance and leads to higher tax evasion. Moreover, corrupt public officials abuse their public power to extort bribes from the private agents. In both types of interaction with the public sector, the private agents are bound to face uncertainty with respect to their disposable incomes. To analyse effects of this uncertainty, a stochastic dynamic growth model with the public sector is examined. It is shown that deterministic excessive red tape and corruption deteriorate the growth potential through income redistribution and public sector inefficiencies. Most importantly, it is demonstrated that the increase in corruption via higher uncertainty exerts adverse effects on capital accumulation, thus leading to lower growth rates.
as an independent variable. Last in Zellner [10], it is shown that equations of simultaneous equation models can be brought into a regression form involving some observable and some unobservable independent variables. Given that regression relationstcontaining unobservable independent variables occur quite frequently, and -in' fact are a special case of "errors in the variables" models, it is important to have good methods for analyzing them. Previous analyses have almost always involved the use of an instrumental variable approach, an approach which leads to estimators with the desirable large sample property of consistency. However, it is not clear that the instrumental variable approach leads to asymptotically efficient estimators for all parameters of a model and the small sample properties of instrumental variable estimators are for the most part unknown. In the present paper, we first consider the specification and interpretation of the models under consideration in Section 2. Then in Section 3 we apply a least squares approach to generate an estimator which, with a normality assumption, is a maximum likelihood estimator. The relationship of this estimator to certain instrumental variable estimators is set forth. Then in Section 4, a Bayesian analysis of the model is presented. Finally, in Section 5 some concluding remarks are presented.
Traditional econometric models assume a constant one-period forecast variance. To generalize this implausible assumption, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced in this paper. These are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances. For such processes, the recent past gives information about the one-period forecast variance. A regression model is then introduced with disturbances following an ARCH process. Maximum likelihood estimators are described and a simple scoring iteration formulated. Ordinary least squares maintains its optimality properties in this set-up, but maximum likelihood is more efficient. The relative efficiency is calculated and can be infinite. To test whether the disturbances follow an ARCH process, the Lagrange multiplier procedure is employed. The test is based simply on the autocorrelation of the squared OLS residuals. This model is used to estimate the means and variances of inflation in the U.K. The ARCH effect is found to be significant and the estimated variances increase substantially during the chaotic seventies.
This paper studies estimators that make sample analogues of population orthogonality conditions close to zero. Strong consistency and asymptotic normality of such estimators is established under the assumption that the observable variables are stationary and ergodic. Since many linear and nonlinear econometric estimators reside within the class of estimators studied in this paper, a convenient summary of the large sample properties of these estimators, including some whose large sample properties have not heretofore been discussed, is provided.
This note shows that, in the structural neutrality version of the linear rational expectations model, the parameters measuring the strength of response to unanticipated shocks cannot be identified in the absence of restrictions on the covariance properties of the structural disturbances. The consequences of this result for the commonly used two-step estimation method are explored.
The implications for applied econometrics of the assumption that unobservable expectations are formed rationally in Muth's sense are examined. The statistical properties of the resulting models and their distributed lag and time series representations are described. Purely extrapolative forecasts of endogenous variables can be constructed, as alternatives to rational expectations, but are less efficient. Identification and estimation are considered: an order condition is that no more expectations variables than exogenous variables enter the model. Estimation is based on algorithms for nonlinear-in-parameters systems; other approaches are surveyed. Implications for economic policy and econometric policy evaluation are described.
The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the ‘theory first’ versus the ‘data first’ perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander’s argument in his paper “Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics” contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories.
The efficient estimation of econometric models with rational expectations by the substitution method usually entails the use
of a non-linear simultaneous equations estimator and hence is not very attractive computationally. It is shown that for a
wide class of problems efficient estimates can also be obtained with standard estimation methods if instead an errors in variables
approach is used. For many other problems, although not providing fully efficient estimates because rationality is not imposed,
the errors in variables method will still have a strong appeal because otherwise it uses all of the structural information
in the model; unlike the substitution method, when an incomplete information set is used, it guarantees consistent estimates;
and it is easy to compute.
This paper examines the relationship between the post-tax real interest rate and the Australian household saving ratio at the empirical level. Using alternative models of the consumption-saving decision and different estimation periods, it is shown that the post-tax real interest rate exerts a significant negative influence on the saving ratio. The estimates, therefore, imply that the fall in post-tax real interest rates during the 1970s contributed to the rise in the Australian saving ratio.
Rational Expectations, Monetary Policy and the Natura.1 Rate of Unemployment in Australia
- J I Horne
- Mcdonald
HORNE, J. AND I. MCDONALD, "Rational Expectations, Monetary Policy and the Natura.1
Rate of Unemployment in Australia," Discussion Paper, 9th Conference of Economists,
Brisbane (1980).
Output, Expected Demand and Unplanned Stocks
- G J Anderson
- I F Pearce
- P K Trivedi
ANDERSON, G. J., I. F. PEARCE AND P. K. TRIVEDI, "Output, Expected Demand and Unplanned Stocks," in, I. F. Pearce et al., eds., A Model of Output, Employment, Wages and Prices in the U.K. (Cambridge: Cambridge University Press, 1976).
The Wage Equation and Rational Expectations
- P M Minford
- Brech
MINFORD, P. AND M. BRECH, "The Wage Equation and Rational Expectations" in, D. Currie,
R. Nobay and D. Peel, eds., Macroeconomic Analysis (London: Croom Helm, 1981),
434-459.
Uncertainty in the Demand for Money During Hyperinflation
- P C B Phillips
- M R And
- P Wickens Poulter
PHILLIPS, P. C. B. AND M. R. WICKENS, Problemns anid Exercises in Econiomiietrics (London: Phillip Allen, 1978), Vol. 1. POULTER, P., "Uncertainty in the Demand for Money During Hyperinflation," Economic Inquiry, 19 (1981), 165-172.
The Determination of the Rate of Change of Wages and Prices in the Fixed Exchange Rate World Economy
- N Duck
- M Parkin
- D Rose And G
- Zis
DUCK, N., M. PARKIN, D. ROSE AND G. ZIS, "The Determination of the Rate of Change of
Wages and Prices in the Fixed Exchange Rate World Economy, 1956-1971," in, M. Parkin
and G. Zis, eds., Ir~flatiorz in the World Ecoriomj~ (Manchester: Manchester University
Press, 1976).
Asymptotic Properties of Maximum Likeli-hood Estimators for Stochastic Processes This content downloaded from 152.3.102.242 on Fri, 11 Oct 2013 09:47:27 AM All use subject to JSTOR Terms and Conditions AMartingale Central Limit Theorems
- I V Basawa
- P D Feigin And
- C C Heyde
- B M Pagan Brown
BASAWA, I. V., P. D. FEIGIN AND C. C. HEYDE, "Asymptotic Properties of Maximum Likeli-hood Estimators for Stochastic Processes," Sankhya, 38 (January, 1976), 259-270. This content downloaded from 152.3.102.242 on Fri, 11 Oct 2013 09:47:27 AM All use subject to JSTOR Terms and Conditions A. PAGAN BROWN, B. M., "Martingale Central Limit Theorems," Annals of Mathematical Statistics, 42 (February, 1971), 59-66.
Econon7etric Methods
- J Johnston
JOHNSTON, J., Econon7etric Methods, 2nd ed. (New York: McGraw Hill, 1972).
org/sici?sici=0022-3808%28197708%2985%3A4%3C691%3ATDFQCB%3E2.0.CO%3B2-D Rational Expectations and the Estimation of Econometric Models Charles R
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Rational Expectations and the Estimation of Econometric Models
Charles R. Nelson
International Economic Review, Vol. 16, No. 3. (Oct., 1975), pp. 555-561.
org/sici?sici=0012-9682%28198001%2948%3A1%3C49%3AEIOTRE%3E2.0.CO%3B2-E The Efficient Estimation of Econometric Models with
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The Efficient Estimation of Econometric Models with Rational Expectations
M. R. Wickens
The Review of Economic Studies, Vol. 49, No. 1. (Jan., 1982), pp. 55-67.
jstor.org/sici?sici=0022-3808%28197604%2984%3A2%3C207%3AACMMFT%3E2.0.CO%3B2-Q Econometric Implications of the Rational Expectations Hypothesis Kenneth F
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Econometric Implications of the Rational Expectations Hypothesis
Kenneth F. Wallis
Econometrica, Vol. 48, No. 1. (Jan., 1980), pp. 49-73.
The reference numbering from the original has been maintained in this citation list. A Classical Macroeconometric Model for the United States Thomas
NOTE: The reference numbering from the original has been maintained in this citation list.
A Classical Macroeconometric Model for the United States
Thomas J. Sargent
The Journal of Political Economy, Vol. 84, No. 2. (Apr., 1976), pp. 207-238.
The Measurement of Long-and Short-Tern1 Price Uncertainty: A Moving Regression Time Series AnalysisMacroeconometric of Rational and Neutrality Hypothesis for the United States
,"The Measurement of Long-and Short-Tern1 Price Uncertainty: A Moving Regression
Time Series Analysis," Economic Inquiry, 16 (1978), 438452.
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