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Corruption has been one of the challenging topics in public economics for years, prompting extensive discussions from various perspectives. In this study, we investigate the causal relationship between government size and corruption in Turkey, where the anticorruption performance has been getting worse over time until recently. By utilizing a long-span news-based corruption index spanning approximately three-quarters of a century, we conclude that government size serves as the long-term driving force behind corruption in Turkey from 1950 to 2019. This conclusion is robustly reached through a battery of dynamic time series analyses. [ABSTRACT FROM AUTHOR]

This study investigates the determinants of trading activity in the U.S. corporate bond market, focusing on the effects of Seasonal Affective Disorder (SAD) and macroeconomic announcements. Employing the General-to-Specific (Gets) Autometrics methodology, we identify distinct behavioral responses between retail and institutional investors to SAD, noting a significant impact on retail trading volumes but not on institutional trading or bond returns. This discovery extends the understanding of behavioral finance within the context of bond markets, diverging from established findings in equity and Treasury markets. Additionally, our analysis delineates the influence of macroeconomic announcements on trading activities, offering new insights into the market's reaction to economic news. This study's findings contribute to the broader literature on market microstructure and behavioral finance, providing empirical evidence on the interplay between psychological factors and macroeconomic information flow within corporate bond markets. By addressing these specific aspects with rigorous econometric techniques, our research enhances the comprehension of trading dynamics in less transparent markets, offering valuable perspectives for academics, investors, risk managers, and policymakers. [ABSTRACT FROM AUTHOR]

This article undertakes a literature review on the topic of market integration, covering over 380 articles from the 1980s to 2024. The review consists of a qualitative analysis for context and a quantitative analysis for content, identifying key research streams and proposing directions for future research. I have identified six research groups: (1) market segmentation, (2) portfolio diversification, (3) market integration evidence from developed and emerging markets, (4) spillovers and linkages, (5) economic market integration, and (6) financial market integration and volatility. The literature focuses on market integration; it aims to answer the following questions: (1) What is the scope of market integration research? (2) What are the direct influences of market integration looking at top journals and authors and characteristics of most studied and cited topics? (3) What are the past and recent topics studied within the area of market integration? (4) What are the potential future research questions to explore in market integration? The topic of market integration has been controversial in many studies, as seen in policy decision-making, investments, and other related areas; this literature will provide great benefit for such an audience. [ABSTRACT FROM AUTHOR]

Agricultural baselines facilitate policy and investment decisions by governments and market participants by providing long‐term projections about the farm sector. Despite their importance in shaping agricultural policy, the agricultural baselines have not been rigorously evaluated. This study evaluates the accuracy and informativeness of two widely used baselines for the US farm sector published by the United States Department of Agriculture (USDA) and the Food and Agricultural Policy Research Institute (FAPRI) in three steps. First, we examine the average percent errors of the projections and perform tests of bias. Second, we use a testing framework based on the encompassing principle to test the predictive content of the projections for each horizon, determining the longest informative projection horizon. Third, we compare the USDA and FAPRI baseline projections using a multi‐horizon framework that considers all projection horizons jointly. We find that prediction error and bias increase with the horizon's length. The predictive content of the baselines projections for most variables diminishes after 4–5 years. The multi‐horizon comparison suggests that neither USDA nor FAPRI projections have uniform or average superior predictive ability over the other for most variables. Our findings are useful for the agencies producing these baselines and for the policymakers, agricultural businesses, and other stakeholders who use them. The study contributes to the recent literature on long‐term agricultural projections and establishes the groundwork for future research inquiries. [ABSTRACT FROM AUTHOR]

Milton Friedman is usually presented as an economist characterized by his empirical approach to economics. His binary classification of economics into positive means and normative ends relies on the empirical content of predictions. Throughout his career, he used extensive, data-based statistical techniques. While important scholarly attention has been devoted to Friedman's academic and political trajectories, his methodological prescriptions, and the development of economics at the University of Chicago, we know much less about the interplay of these elements. This paper proposes an intertwined reading of them. My aim is threefold. First, to understand Friedman's work and methodological choices, I relate his empirical approach to his early training in statistics. Second, I articulate Friedman's understanding of economics as an empirical policy science in the process of building the image of economists as neutral advisers in the policy-making process. Third, I claim that Friedman's empirical methodological framework, developed while he was in the Economics Department of the University of Chicago, established the guidelines for an institutional long-term project that shaped it. [ABSTRACT FROM AUTHOR]

In this paper, we address whether using a disaggregated series or combining an aggregated and disaggregated series improves the forecasting of the aggregated series compared to using the aggregated series alone. We used econometric techniques, such as the weighted lag adaptive least absolute shrinkage and selection operator, and Exponential Triple Smoothing (ETS), as well as the Autometrics algorithm to forecast industrial production in Brazil one to twelve months ahead. This is the novelty of the work, as is the use of the average multi-horizon Superior Predictive Ability (aSPA) and uniform multi-horizon Superior Predictive Ability (uSPA) tests, used to select the best forecasting model by combining different horizons. Our sample covers the period from January 2002 to February 2020. The disaggregated ETS has a better forecast performance when forecasting horizons that are more than one month ahead using the mean square error, and the aggregated ETS has better forecasting ability for horizons equal to 1 and 2. The aggregated ETS forecast does not contain information that is useful for forecasting industrial production in Brazil beyond the information already found in the disaggregated ETS forecast between two and twelve months ahead. [ABSTRACT FROM AUTHOR]

Aggregate financial conditions indices (FCIs) are constructed to fulfil two aims: (i) The FCIs should resemble non-model-based composite indices in that their composition is adequately invariant for concatenation during regular updates; (ii) the concatenated FCIs should outperform financial variables conventionally used as leading indicators in macro models. Both aims are shown to be attainable once an algorithmic modelling route is adopted to combine leading indicator modelling with the principles of partial least-squares (PLS) modelling, supervised dimensionality reduction, and backward dynamic selection. Pilot results using US data confirm the traditional wisdom that financial imbalances are more likely to induce macro impacts than routine market volatilities. They also shed light on why the popular route of principal-component based factor analysis is ill-suited for the two aims. [ABSTRACT FROM AUTHOR]

A theory-consistent CVAR scenario describes a set of testable regularities capturing basic assumptions of the theoretical model. Using this concept, the paper considers a standard model for exchange rate determination with forward-looking expectations and shows that all assumptions about the model's shock structure and steady-state behavior can be formulated as testable hypotheses on common stochastic trends and cointegration. The basic stationarity assumptions of the monetary model failed to obtain empirical support. They were too restrictive to explain the observed long persistent swings in the real exchange rate, the real interest rates, and the inflation and interest rate differentials. [ABSTRACT FROM AUTHOR]

We propose a method to explore the causal transmission of an intervention through two endogenous variables of interest. We refer to the intervention as a catalyst variable. The method is based on the reduced-form system formed from the conditional distribution of the two endogenous variables given the catalyst. The method combines elements from instrumental variable analysis and Cholesky decomposition of structural vector autoregressions. We give conditions for uniqueness of the causal transmission. [ABSTRACT FROM AUTHOR]

Recently, studies have highlighted the importance of a holistic digitalisation that incorporates process digitalisation, product digitalisation as well as digital transformation involving redefinitions of business models and organisational identities. Whereas previous studies either aimed for generalisability across firms, or investigated digital transformation projects in particular industries, only very few studies investigated the particularities of family businesses (i.e., family influence) in the digitalisation context. Based on a unique dataset of 164 German family firms, our study sheds light on the role of family ability and family willingness for holistic digitalisation. Our results show that product digitalisation is statistically independent from family influence. Whereas process digitalisation benefits only from family ability, digital tranformation is bound to the families' willingness to pursue the transformation. [ABSTRACT FROM AUTHOR]

The name I Cobb-Douglas i derives from Douglas's first published time-series study with Cobb (Cobb and Douglas [14]), after which Cobb ceased to participate. En route, Hendrik Houthakker ([45]) (who references Horst Mendershausen's highly critical [61] article on Douglas's production function research) had established that aggregating microlevel Leontief production functions could lead to macro Cobb-Douglas. Biddle remarks that "the original time-series regression of the 1928 Cobb-Douglas paper arose out of Douglas's prior research interests and represented cutting-edge work in empirical economics" (4). Chapter 5 discusses the take up of the Cobb-Douglas production function in agricultural economics, which kept associated research work alive while Douglas was in the Senate. [Extracted from the article]

Policy responsiveness to public opinion is necessary for democratic governance, yet research on crime policy responsiveness has focused on the public at large, overlooking variation in policy support among demographic bodies and its heterogeneous effects on policy implementation. Creating new state-level measures of group opinion on punitive policy mood using 257,356 responses to 79 national surveys administered between 1970 and 2015, this study examines the effect of race, age, and gender-specific opinion on the incarceration rate. Consistent with prior studies, results reveal parallel trends in punitive policy support, with punitiveness increasing in tandem across demographic subgroups. Statistical findings from error correction models, however, reveal that not all groups had equal influence. Only the opinions of the most punitive groups—whites, men, and 30–44-year-olds—influenced the incarceration rate. Further, the largest divide in policy responsiveness to group opinion was between blacks and whites. In fact, estimates suggest that if whites' punitive policy support had not risen, the current incarceration rate would be roughly the same as if violent crime had not risen during the 45 years of mass incarceration. The implications of these results are discussed for research on policy responsiveness, partisan politics, and for the "democracy at work" hypothesis of mass incarceration. [ABSTRACT FROM AUTHOR]

A fundamental challenge facing applied time‐series analysts is how to draw inferences about long‐run relationships (LRR) when we are uncertain whether the data contain unit roots. Unit root tests are notoriously unreliable and often leave analysts uncertain, but popular extant methods hinge on correct classification. Webb, Linn, and Lebo (WLL; 2019) develop a framework for inference based on critical value bounds for hypothesis tests on the long‐run multiplier (LRM) that eschews unit root tests and incorporates the uncertainty inherent in identifying the dynamic properties of the data into inferences about LRRs. We show how the WLL bounds procedure can be applied to any fully specified regression model to solve this fundamental challenge, extend the results of WLL by presenting a general set of critical value bounds to be used in applied work, and demonstrate the empirical relevance of the LRM bounds procedure in two applications. [ABSTRACT FROM AUTHOR]

In this article, the author discusses the properties of useful econometric models for marketing phenomena, with particular attention on models for policy simulations. The author addresses model diagnostics, parameter stability, exogeneity, and the Lucas critique. He also presents the results of a search through the 1998-2003 issues of the Journal of Marketing Research. Finally, the author offers practical guidelines. [ABSTRACT FROM AUTHOR]

The article offers a report that highlights a survey of recent work in the history of econometrics. It mentions that the econometricians have considered historical knowledge as reflexive knowledge useful to delineate their discipline and highlights a coordinated response to a review of Mary Morgan's History of Econometric Ideas.

Following consultations with several Board members of Econometric Reviews, we have decided to recognize major contributors to the journal since its inception in 1982. Authors with a score of 2.5 and above are designated "ER Scholars." These contributors include successive Board Members and editors, and authors whose published works in ER lead to a score of 3 or above. [Extracted from the article]

Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which would in turn question the validity of the entailed policy implementation. We establish when systematic forecast failure entails failure of the accompanying narrative, which we call forediction failure, and when that in turn implies policy invalidity. Most policy regime changes involve location shifts, which can induce forediction failure unless the policy variable is super exogenous in the policy model. We propose a step-indicator saturation test to check in advance for invariance to policy changes. Systematic forecast failure, or a lack of invariance, previously justified by narratives reveals such stories to be economic fiction. [ABSTRACT FROM AUTHOR]

Persistent variations of the log price-to-dividend ratio (PD) and their economic determinants have attracted a lively discussion in the literature. We suggest a gradually time-varying state process to govern the persistence of the PD. The adopted state-space approach offers favorable model diagnostics and finds particular support in out-of-sample stock return prediction. We show that this slowly evolving mean process is jointly shaped by the consumption risk, the demographic structure, and the proportion of firms with traditional dividend payout policy during the past 60 years. In particular, the volatility of consumption growth plays the dominant role. [ABSTRACT FROM AUTHOR]

This paper examines how financial deregulation and the partisan underpinnings of deregulation shaped the path of income inequality in the United States. Using time-series data from 1914 to 2010, we assess the effect of partisan politics on financial deregulation and, in turn, the effect of deregulation on income inequality. We find that financial deregulation has generally declined when Democrats attain more power in Washington and that deregulation has contributed to rising inequality. We also learn that the partisan effect on deregulation has diminished since the early 1980s, suggesting that one way partisan politics has contributed to the recent rise in inequality is related to convergence on matters of financial deregulation. We explore several potential explanations for this post–1980 partisan convergence, finding evidence supporting the idea that globalization, the increasing availability of credit, and shifts in campaign finance were contributing factors. [ABSTRACT FROM AUTHOR]