A random walk through the Gibson paradox

Evidence to support the Gibson paradox is often given in the form of a simple correlation between the nominal interest rate and the log of price level, or in the form of a simple linear regression between these two variables. Authors then show, using standard procedures of statistical inference, that the price level possesses a significant coefficient. We argue that this class of evidence is spurious since the nominal interest rate and the price level (both integrated variables) do not form a cointegrated system.     

The causal analysis of contingency tables: A return to first principles

Given the undoubtedly major advances in the analysis of contingency tables which have been achieved over the past ten years or so (see for example, Fienberg, 1980; Upton, 1978; Everitt, 1977; Haberman, 1978, 1979), it might seem rather unnecessary to want to return to first princples again. However, the need arises precisely because of these advances; for progress in the specifically causal analysis of contingency tables has not matched the other advances at all. Whilst Fienberg devoted a chapter to causal analysis, he made it clear that he views “the assignment of numerical values [to the arrows in a path diagram] as problematic, and [he] would limit [the analysis] to an indication of sign for causal relationships, in a fashion similar to that described by Blalock (1964)” (Fienberg, 1980, pp. 91–92). Considering how far quantitative-variable causal analysis has developed since Blalock (1964), it becomes clear that the causal analysis of qualitative data is still at a rather primitive stage. Indeed, Haberman (1978, 1979), in his two-volume survey of the analysis of qualitative data, does not mention it at all. The problem, I believe, is that log-linear and logit methodology are not particularly suited to the logic of causality in contingency tables. In order to derive a suitable method, it is necessary to uncover the logic underlying causality when applied to qualitative variables. A few others have taken seriously the idea that a direct analysis of the form of a contingency table can lead to fruitful results (see, especially, for example, Boudon, 1967), but their work has been overshadowed by the statistically more profound advances made in log-linear methods. This article is an attempt to provide a statistically rigorous analysis based on the direct interpretation of causality embodied in a contingency table.     

Causality in economics: Rhetorical ethic or positivist empiric?

This paper explores the concept of ‘causality’ in the social and behavioural sciences, particularly as deployed in economics and econometrics (or statistical testing in general). Causality is closely associated with empirical testing of theories and hypotheses in an empiricist manner. In this way it is fundamentally connected to our notions of scientific endeavour. But causality is also a rhetorical category in these areas, as well as in everyday debate about social and economic matters. The question raised is ‘Why has causality come to occupy such a central place in our intellectual culture? What are the conditions of existence of a “causal culture” in both the domain of scientific endeavour and popular disputation?’ The argument is that there are a wide range of conditions that support this ‘causal culture’ not least of which is an ethical imperative associated with a felt need to attribute blame for mishaps, accidents, conditions of life, and so on. Thus an ethic of morality is strongly involved. The rhetorical operation of causality is linked to this ethic and, in addition, to a range of other non-ethical conditions for the ‘causality culture’ within economics and related disciplines.     

Institutions and economic development: A Granger causality analysis of panel data evidence

This study examines the causal relationship between institutions and economic development using a panel Granger causality test. The study incorporates two institutional datasets, the International Country Risk Guide (ICRG) and World Governance Indicators (WGI). The empirical results based on 60 countries show that there is a bi-directional causality between institutions and economic development. The findings also suggest that causality patterns between institutions and economic performance vary at different stages of income level. Better institutional quality fosters economic development in higher income countries, whereas economic development tends to enhance institutional quality in lower income countries.     

Temporal causality between house prices and output in the US: A bootstrap rolling-window approach

This paper examines the causal relationships between the real house price index and real GDP per capita in the US, using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and real GDP per capita, covering the period 1963:Q1 to 2012:Q2. The full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from the real house price index to real GDP per capita. A wide variety of tests of parameter constancy used to examine the stability of the estimated vector autoregressive models indicate short- and long-run instability. This suggests that we cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach to examine the causal relationship between these two variables. Using a rolling window size of 28 quarters, we find that while causality from the real house price to real GDP per capita occurs frequently, significant, but less frequent, evidence of real GDP per capita causing the real house price also occurs. These results imply that while the real house price leads real GDP per capita, in general (both during expansions and recessions), significant feedbacks also exist from real GDP per capita to the real house price.     

Further evidence on finance-growth causality: A panel data analysis

This paper reassesses the causal relationship between financial development and economic growth. Using recently developed panel methods on a data set of 71 developed and developing countries over the period 1960-2004, our study confirms previous results of a bidirectional causality between finance and growth. In addition, we show significant differences among country groups when considering both long-run and short-run causality. While in low and middle income countries there is no supportive evidence of short-run causality between financial development and economic growth, in high income countries economic growth significantly affects financial development.     

Electricity consumption and economic growth empirical evidence from Pakistan

The present article uses the Autoregressive Distributed Lag (ARDL) bounds testing procedure to identify the long run equilibrium relationship between electricity consumption and economic growth. Toda Yamamoto and Wald-test causality tests have identified the direction of the causal relationship between these two variables in the case of Pakistan in the period between 1971 and 2008. Ng-Perron and Clement-Montanes-Reyes unit root tests are used to handle the problem of integrating orders for variables. The results suggest that the two variables are in a long run equilibrium relationship and economic growth leads to electricity consumption and not vice versa.     

Causality and Causal Models: A Conceptual Perspective*

This paper aims at displaying a synthetic view of the historical development and the current research concerning causal relationships, starting from the Aristotelian doctrine of causes, following with the main philosophical streams until the middle of the twentieth century, and commenting on the present intensive research work in the statistical domain. The philosophical survey dwells upon various concepts of cause, and some attempts towards picking out spurious causes. Concerning statistical modelling, factorial models and directed acyclic graphs are examined and compared. Special attention is devoted to randomization and pseudo‐randomization (for observational studies) in view of avoiding the effect of possible confounders. An outline of the most common problems and pitfalls, encountered in modelling empirical data, closes the paper, with a warning to be very cautious in modelling and inferring conditional independence between variables.     

混频Granger因果关系检验的功效和稳健性分析

研究目标：分析混频Granger因果关系检验的功效及其稳健性。研究方法：以货币与产出间的因果关系为例,比较分析不同情形下,混频和同低频Granger因果关系检验功效的差异性和检验结果的稳健性。研究发现：货币与产出间的因果关系不是一成不变的,混频Granger因果关系检验的水平和功效随着不同层次的货币供给、模型滞后阶数、预测期长度,变量的多寡,以及样本量的大小和所处的经济阶段的变化而呈现异质性和非对称性。研究创新：将混频技术与Granger因果关系结合起来,从不同角度全面系统地检验了货币与产出的因果关系,并分析了该方法的稳健性。研究价值：进行货币政策调控时,须评估不同情形下货币政策的作用效果,选取恰当的时机,采用更加合理的调控手段和方法。     

Investor sentiment and Bitcoin relationship: A quantile-based analysis

This paper applies a quantile-based analysis to investigate the causal relationships between Bitcoin and investor sentiment by considering the possible effects of the ongoing COVID-19 pandemic. Such an analysis allows investigating the predictive power of investor sentiment (Bitcoin) on Bitcoin (investor sentiment) at different levels of the distributions. Results emphasize that only Bitcoin returns/volatility have significant predictive power on the investor sentiment whether investors are fear or greed before and over the COVID-19 period. Moreover, the COVID-19 crisis has no effect on the causal relationship between the two variables. Further analysis shows an asymmetric causality observed only during the pandemic period. Furthermore, the quantile autoregressive regression model shows a significant positive relationship between investor sentiment and Bitcoin returns.     

Multivariate-based Granger causality between financial deepening and poverty: the case of Pakistan

This paper deals with the empirical investigation of causal relationship between financial deepening, economic growth and poverty reduction using quarter frequency data in case of Pakistan over the period of 1972–2011. We applied the autoregressive distributed lag model bounds testing approach by incorporating structural breaks stemming in the series. The order of integration of the variables is examined by applying structural break unit root test. Our empirical exercise indicated that the long run relationship between financial deepening, economic growth and poverty reduction exists in case of Pakistan. The causality analysis implied that causality results are sensitive with the use of proxy for poverty reduction.     

Managing risk symptom: A method to identify major risks of serious problem projects in SI environment using cyclic causal model

Serious problem projects (SPPs) often occur, particularly in a system integration environment, and it is difficult to prevent them, since the relationships among phenomena that occur throughout the project life cycle are extremely complicated. Our goal is to make it easier to identify major risks by distinguishing phenomena that are sources of future SPPs from phenomena observed in actual field projects. By choosing several events whose causal relation is known to be cyclic, we constructed a causal model and clarified that it can contribute to the easier recognition of SPPs empirically, by analyzing actual SPP cases.     

CAUSAL INFERENCE ON EDUCATION POLICIES: A SURVEY OF EMPIRICAL STUDIES USING PISA,TIMSS AND PIRLS

The identification of the causal effects of educational policies is the top priority in recent education economics literature. As a result, a shift can be observed in the strategies of empirical studies. They have moved from the use of standard multivariate statistical methods, which identify correlations or associations between variables only, to more complex econometric strategies, which can help to identify causal relationships. However, exogenous variations in databases have to be identified in order to apply causal inference techniques. This is a far from straightforward task. For this reason, this paper provides an extensive and comprehensive overview of the literature using quasi‐experimental techniques applied to three well‐known international large‐scale comparative assessments, such as PISA, PIRLS or TIMSS, over the period 2004–2016. In particular, we review empirical studies employing instrumental variables, regression discontinuity designs, difference in differences and propensity score matching to the above databases. Additionally, we provide a detailed summary of estimation strategies, issues treated and profitability in terms of the quality of publications to encourage further potential evaluations. The paper concludes with some operational recommendations for prospective researchers in the field.     

中国三大都市圈经济增长趋于收敛还是发散?——基于协整分析和Granger因果检验

本文采用Engle和Granger(1987)提出的协整检验方法和Im、Pesaran和Shin(1997)的方法,从时间序列分析角度入手,研究目标是在不同的空间尺度上(全国和三大都市圈),从不同的时间尺度上揭示中国区域经济差异的演化规律。探索改革开放以来三大都市圈区域经济不平衡程度的演化历程与变化趋势。主要结论:长三角和珠三角具有收敛趋势而环渤海都市圈内不存在收敛;三大都市圈之间不存在收敛趋势,在长期受两个共同冲击的影响。     

Impact of economic growth volatility on income inequality: ASEAN experience

The study attempts to examine the symmetric and the asymmetric impact of volatility of economic growth on the inequality of income in the major ASEAN economies over the period 1980–2015. Financial development, trade openness as a proxy of globalization, inflation, human capital formation, and fiscal policy are utilized as major control variables. The paper tries to explore the causal association between inequality of income distribution and economic growth volatility, exploring simultaneously the long-run association and the short-run dynamics in the time series structure. The study applied Clemente–Montanes–Reyes unit root test to identify the structural break in the time series. Further, the cointegrating relationship of the time series observations was explored by applying the ARDL (linear) bounds test approach along with the nonlinear ARDL for making fruitful comparisons in the long-run relationship among the variables. The countries chosen are Malaysia, Indonesia, Thailand, Singapore and The Philippines. The empirical findings strongly suggest a long-run cointegrating relationship between income inequality and growth volatility with a positive and statistically significant impact. Also, the causality analysis was explored using the Toda and Yamamoto (1995) method of Granger causality. The causality test shows that there exists bidirectional causality from inequality transmission to economic growth volatility. The implications that are developed from this study helps us to understand the various policy reforms in the ASEAN region, that are more transparent and can make these economies less susceptible to risks.     

Energy consumption, CO2 emissions, and economic growth: evidence from Indonesia

Energy policy-makers in Indonesia are interested in the causal relationship between energy consumption, CO₂ emissions, and economic growth. Therefore, this paper attempts to analyze the short- and long-run causality issues between energy consumption, CO₂ emissions, and economic growth in Indonesia using time-series techniques. To this end, annual data covering the period 1965–2006 are employed and tests for unit roots, co-integration, and Granger-causality based on an error-correction model are applied. The results show that there is a bi-directional causality between energy consumption and CO₂ emissions. This means that an increase in energy consumption directly affects CO₂ emissions and that CO₂ emissions also stimulate further energy consumption. In addition, the results support the occurrence of uni-directional causality running from economic growth to energy consumption and to CO₂ emissions without any feedback effects. Thus, energy conservation and/or CO₂ emissions reduction policies can be initiated without the consequent destructive economic side effects.     

Export-led economic growth and the case of Brazil: An empirical research

The world has been globalized much more than ever before and this process integrates the economies of countries. Moreover, one means of integrating the economies of countries is trade. In this instance, the export-led economic growth emerges as a considerable determinant. Export-led economic growth is beneficial for the countries since it facilitates the inflow of foreign exchange, increases production, creates new employment opportunities and enhances the overall commercial volume. In this study, the correlation between export-led economic growth is explored for Brazil. Therefore, according to the findings of this paper as well as econometric and statistical applications, there is a bi-directional causality in Brazil since 1960s between economic development and exports in the long-run (this could also be termed as feedback); furthermore, in the short-run, there is export-led economic growth. The novelty of this paper is that, it is one of the latest studies investigating export-led economic growth for Brazil.     

Foreign direct investment and its determinants: A regional panel causality analysis

Moving beyond traditional one- or possibly two-way causality involving foreign direct investment (FDI), a systematic approach is implemented for delineating both short- and long-run flows of causality involving FDI and a comprehensive set of FDI's possible determinants. Granger causality procedures incorporating error correction terms are implemented, using provincial panel data from China. In both the short and long run, growth in GDP directly influences FDI, while growth in local infrastructure and local investment provide indirect but not direct influence.     

Statistical Causality and Strategic Behavior in Industrial Markets

This paper proposes a simple test of the leader-follower model of strategic behavior. This test relates the temporal notions of leadership central to such models to the empirical methods of statistical causality. This test is performed using data from the US softwood plywood industry of the last three decades. Others have productively explored the spatial pricing practices of this industry by applying a leader-follower model. Similarly, we find that a leader-follower model explains well the temporal relations between key strategic variables (prices) in the industry. We conclude that the leader-follower model imposes meaningful restrictions on observable time-series data and that statistical causality is a useful method for testing these restrictions.     

Causality: a Statistical View

Statistical aspects of causality are reviewed in simple form and the impact of recent work discussed. Three distinct notions of causality are set out and implications for densities and for linear dependencies explained. The importance of appreciating the possibility of effect modifiers is stressed, be they intermediate variables, background variables or unobserved confounders. In many contexts the issue of unobserved confounders is salient. The difficulties of interpretation when there are joint effects are discussed and possible modifications of analysis explained. The dangers of uncritical conditioning and marginalization over intermediate response variables are set out and some of the problems of generalizing conclusions to populations and individuals explained. In general terms the importance of search for possibly causal variables is stressed but the need for caution is emphasized.