Dynamic Conditional Correlations in Political Science

Time-varying relationships and volatility are two methodological challenges that are particular to the field of time series. In the case of the former, more comprehensive understanding can emerge when we ask under what circumstances relationships may change. The impact of context—such as the political environment, the state of the economy, the international situation, etc.—is often missing in dynamic analyses that estimate time-invariant parameters. In addition, time-varying volatility presents a number of challenges including threats to inference if left unchecked. Among time-varying parameter models, the Dynamic Conditional Correlation (DCC) model is a creative and useful approach that deals effectively with over-time variation in both the mean and variance of time series. The DCC model allows us to study the evolution of relationships over time in a multivariate setting by relaxing model assumptions and offers researchers a chance to reinvigorate understandings that are tested using time series data. We demonstrate the method's potential in the first example by showing how the importance of subjective evaluations of the economy are not constant, but vary considerably over time as predictors of presidential approval. A second example using international dyadic time series data shows that the story of movement and comovement is incomplete without an understanding of the dynamics of their variance as well as their means.     

Gone with the Wind: Federalism and the Strategic Location of Air Polluters

In federal systems, both state governments and firms have incentives to strategically locate polluting facilities where the environmental and health consequences will be borne as much as possible by residents of other jurisdictions. We analyze air polluter location in the United States using a spatial point pattern model, which models where events occur in latitude and longitude. Our analyses indicate that major air polluters are significantly more likely to be located near a state's downwind border than a control group of other industrial facilities, results that are robust to a wide variety of model specifications and measurement strategies. This effect is particularly pronounced for facilities with toxic air emissions. The observed pattern of polluter location varies systematically across states and time in ways that suggest it is responsive to public policy at both the national and state levels.     

Rough Terrain: Spatial Variation in Campaign Contributing and Volunteerism

We examine spatial patterns of mass political participation in the form of volunteering and donating to a major statewide election campaign. While these forms of participation are predictably associated with the political and socioeconomic characteristics of the precincts in which the participants reside, we find that these statistical relationships are spatially nonstationary. High-income neighborhoods, for example, are associated with stronger effects on participation at some locations more than at others. By using geographically weighted regression (GWR) to specify local regression parameters, we are able to capture the heterogeneity of contextual processes that generate the geographically uneven flow of volunteers and contributors into a political campaign. Since spatial nonstationarity may well be a rule rather than an exception in the study of many political phenomena, social scientific analyses should be mindful that relationships may vary by location.     

Investments in Global Warming Mitigation: The Case of “Activities Implemented Jointly”

This paper examines bilateral cooperation between developed countries (home country) and developing countries (host country) to reduce greenhouse gas emissions and to enhance carbon dioxide sinks. With the home-host country pair as the unit of analysis, our logistic regression model examines 158 Activities Implemented Jointly (AIJ) investment projects from 1993 until 2002 across 2541 country-pairs. Because the marginal costs of reducing emissions may be lower in developing countries, the AIJ projects served as a policy laboratory to assess whether such investments might be advantageous to both countries in the event future regimes allowed emission credits from such bilateral projects. Instead of investing in home countries where maximum pollution reductions (or carbon sequestration) might be possible, home countries invest in locations where they can conduct their policy experiments at low transaction costs. Prior trade and aid relationships were used as a proxy. Regarding energy projects, location decisions are driven by home countries’ desire to reduce air pollution that they receive from abroad. Geography – proximity of a host country to a home country – in interaction with host country's coal production, is a very important driver of location decision in AIJ energy sector projects. Location of sequestration projects is impacted by the host country's potential for avoiding deforestation as well as by previous aid and trade patterns between a home and a host country. Proximity is not important in this case.     

Economic performance and U.S. Senate elections: Reply

Major criticisms made by Chressanthis and Shaffer (C-S) are addressed: the authors' failure to include noneconomic variables in the regression model, the inclusion of open elections in the sample, and the use of variables other than the state unemployment rate as economic performance measures. Errors in C-S's interpretations are noted. Additional regression results are reported using modifications of the authors' original model. These suggest that the change (notrelative change as in C-S) in state unemployment rate is superior, and that the authors' model yields a stronger effect of state economic performance on election outcomes than does the C-S model.John Beck contributed helpful comments.     

Nash equilibrium strategies in directional models of two- candidate spatial competition

The standard approach to two-party political competition in a multi-dimensional issue space models voters as voting for the alternative that is located closest to their own most preferred location. Another approach to understanding voter choice is based on preferred direction of change with respect to some specified neutral point (e.g., an origin or status quo point). For the two-dimensional Matthews directional model (Matthews, 1979), we provide geometric conditions in terms of the number of medians through the neutral point for there to be a Condorcet (undominated) direction. In this two-dimensional setting, the set of residual locations for which no Condorcet directions exist is identical to the null dual set (Schofield, 1978) and to the heart (Schofield, 1993). In two dimensions, for most locations of the origin/status quo point, a Condorcet direction exists and points toward the yolk, a geometric construct first identified by McKelvey (1986). We also provide some simulation results on the size of the null dual set in two dimensions when the underlying distribution of points is non-symmetric.     

Who Needs Leaders the Most? The Interactive Effect of Leadership and Core Self-Evaluations on Commitment to Change in the Public Sector

ABSTRACT

The purpose of this article is to shed light on an understudied topic in public administration, namely, commitment to organizational change. Specifically, this study examines the extent to which the quality of the relationship between employees and their managers positively influences employees’ commitment to change. Further, it investigates whether this relationship varies as a function of a person's core self-evaluations, that is, the valence of a person's self-regard. Evidence from a multivariate regression analysis in a public sector organization at the local level in the UK revealed that individuals who have high-quality relationships with their managers are more likely to be accepting of change; this is especially true for individuals with lower levels of core self-evaluations. Implications for theory and practice are discussed.     

Unbundling R&D and Manufacturing: Postindustrial Myth or Economic Reality?

Understanding determinants of business location decisions is important from the point of view of economic policy. While the determinants of manufacturing and R&D location have been extensively covered in the literature, in this article we examine a largely neglected question: Under what conditions do manufacturing and R&D have to be physically colocated, that is, when is unbundling the two impossible? In a sample of 241 Finnish industrial firms, we find that unbundling R&D and manufacturing is possible for some companies but indeed a postindustrial myth of sorts for many others. The need for colocation correlates with knowledge intensity of activities: product complexity, process complexity, and industry rate of change, but interestingly enough, not with the size of the firm's R&D budget.     

Pluralistic project design

The improved valuation techniques that have expanded the range of benefit-cost analysis assume the likelihood and intensities of impacts from development projects can be predicted. Techniques for prediction address the impacts of the project on the environment and society, but indirect relationships - the impact on society and thereby the environment - are too numerous, subtle, and complex to model. Even if these indirect relationships could be modeled systematically, predictive models must assume factors and relationships are fixed or change in predetermined ways. Projects do not perform as predicted and benefit-cost analyses have limited value because the characteristics of factors and relationships in fact evolve in unpredictable ways over time. In some cases evolution results in further gains, but typically this has not been the case. The use of coevolutionary development criteria would help in the design of projects which would more likely evolve in preferred ways.     

Legitimacy crises and the temporal dynamics of bureaucratic representation

The representation of specific groups and social interests within (or by) the civil service has long been a concern of public administration scholarship. Yet, much of this literature focuses on representation at a single point in time. In this article, we propose a more dynamic perspective. In terms of theory, we postulate specific temporal relationships between triggering cues (e.g., a crisis event) and the representation decisions of civil servants. We specify two complementary mechanisms underlying these relationships: that is, a sensemaking process whereby the perceived meaning and relative salience of distinct groups and interests changes over time; and a shift in bureaucrats' discretion to represent specific groups or interests changes over time. We illustrate these time-dependent processes using interview and survey data from the European Commission.     

Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999

At the heart of attitudinal and strategic explanations of judicialbehavior is the assumption that justices have policy preferences.In this paper we employ Markov chain Monte Carlo methods tofit a Bayesian measurement model of ideal points for all justicesserving on the U.S. Supreme Court from 1953 through 1999. Weare particularly interested in determining to what extent idealpoints of justices change throughout their tenure on the Court.This is important because judicial politics scholars oftentimesinvoke preference measures that are time invariant. To investigatepreference change, we posit a dynamic item response model thatallows ideal points to change systematically over time. Additionally,we introduce Bayesian methods for fitting multivariate dynamiclinear models to political scientists. Our results suggest thatmany justices do not have temporally constant ideal points.Moreover, our ideal point estimates outperform existing measuresand explain judicial behavior quite well across civil rights,civil liberties, economics, and federalism cases.     

中国社会转型下的心理福利与社会支持

中国以经济体制改革为先导的社会转型,对社会生活的各方面都产生深刻影响。医疗服务私有化与价格上涨、社会快速流动与分化,可能严重影响民众心理福利。但鲜有研究考察社会转型的心理福利后果及社会支持的调节作用。本文利用2005年中国综合社会调查数据(CGSS2005),检验了医疗支出负担、社会地位及其比较、社会支持同城乡居民心理福利的关系,并在中国性别结构失衡问题日渐暴露的背景下,关注了婚姻作为重要的社会支持机制在其中的角色。结果表明,相对剥夺感对心理福利存在普遍影响,市场化转型更可能损害社会弱势群体的心理福利。在中国转型社会,社会支持对心理福利存在保护功能,且可以缓冲医疗支出负担加大和相对被剥夺地位对农村居民心理福利的负面影响;婚姻的功能角色呈现多元化,既加大了医疗支出负担的负面影响,也强化了其他社会支持的保护作用。研究发现对理解和改善社会转型的心理福利后果,提供了重要的指引和借鉴。     

Understanding Policy Networks: towards a Dialectical Approach

This article has two aims. First, we develop a dialectical model of the role that policy networks play in any explanation of policy outcomes. Our model is based upon a critique of existing approaches and emphasizes that the relationship between networks and outcomes is not a simple, unidimensional one. Rather, we argue that there are three interactive or dialectical relationships involved between: the structure of the network and the agents operating within them; the network and the context within which it operates; and the network and the policy outcome. Second, we use this model to help analyse and understand continuity and change in British agricultural policy since the 1930s. Obviously, one case is not sufficient to establish the utility of the model, but the case does illustrate both that policy networks can, and do, affect policy outcomes and that, in order to understand how that happens, we need to appreciate the role played by the three dialectical relationships highlighted in our model.     

Does India's growth matter? Evidence from the SAARC nations

The study estimates the extent of spillover effects that India's real per capita gross domestic product (GDP) growth rate has on the growth rates of other countries in the South Asian Association for Regional Cooperation (SAARC) region for the period 2003–2016. It also identifies whether the conventional trade channel is the means through which growth is transmitted from India to her neighboring countries. Using a random effects model, we conclude that on average, a 1 percentage point increase in India's real per capita GDP growth rate results in 0.46 percentage point increase in the per capita GDP growth rates of other SAARC nations. However, this does not occur through the trade channel primarily due to low levels of intraregional trade. Also, using time dummies, the paper analyzes whether there has been any significant change in the degree of spillover effects in the postfinancial crisis period, where countries have been observed to insulate themselves to a certain extent.     

USING LINEAR TREND MODELS TO ANALYZE POLICY IMPACT

Policy researchers have become increasingly familiar with a number of improved techniques for analyzing data obtained from interrupted time-series designs for evaluating public programs and policies. In this paper we contribute to this trend by presenting two groups of data analysis techniques which are not currently widely used by policy researchers, but are likely to be valuable adjuncts to traditional regression techniques for analyzing data obtained from interrupted time-series designs. First, aids for model specification are presented that enable the analyst to define an appropriate linear trend model—often one which will reduce the degree of multicollinearity and, therefore, produce more precise estimates of the impacts of a public program or policy. Next we consider approaches for point estimation and joint (simultaneous) interval estimation of a policy intervention's total effect at various points in time.     

Parties under stress: Realignment and dealignment in advanced industrial societies

The findings of a forthcoming study of electoral change in advanced industrial democracies are reviewed. These findings point to broad‐based processes of change that can be organised around two models ‐a social cleavage model of realignment and a functional model of dealignment. Both types of change are at work in most party systems. Surprisingly, their impact on future party system change is likely to be more reinforcing than contradictory in altering the context of party competition and moving parties further away from the responsible party model.     

Ordering Stakeholder Relationships and Citizen Participation: Evidence from the Community Development Block Grant Program

Local administrative professionals typically are accountable to multiple stakeholders, including other governmental units, special interests in the business and nonprofit sectors, and citizens. How are these accountability relationships ordered? What is the position of citizens in that hierarchy, particularly the influence of citizen participation? Focusing on patterns of hearing participation and citizen impact on budgeting decisions for the Community Development Block Grant program, this statistical analysis employs ordered probit regression. The authors find that communities in which grant administrators feel most accountable to citizens for grant performance have higher degrees of citizen participation in hearings and higher levels of perceived citizen impact on budgetary processes. This relationship holds even in the presence of simultaneity between bureaucratic accountability to citizens and citizen participation. The findings point to the importance of instilling a public service ethic among government employees that places a high value on engaging as well as listening to citizens.     

The unacceptable inconstancy of data

The theory of modernization can be combined with historical structural analysis into a single explanatory schema to account for the determinants of migration. The pertinence of data with respect to the proposals contained in the theory is also discussed. The author illustrates an approximation between the kind of questions used in the investigation and the kind of answers delivered by various statistical instruments. Current problems of methodology such as the construction of data and analysis and diachronic-synchronic levels are discussed. Cortes states that 1) mechanical application of any technical statistics without considering the validity of the assumptions on which it is based or structure type produces invalid information and empirical answers without theoretical significance if structural felicity and the conjunction of theoretical relationships are not considered; 2) the internal connection between the various areas of social activities gives rise in empirical social investigation to matrices of data with high intercorrelation; 3) simple correlation analysis has serious limitations and can induce erroneous results from data due to the absence of control mechanisms; and 4) controlling the effect of other variables which may obscure the net effects of one variable over another happens at the moment of generating occurrences or through statistical control for which it is necessary to incorporate those variables in the analysis. Cortes uses the multiple linear regression model to control the effect of the other variables and uses partial correlation instead of regression coefficients. For the theory of migration this investigation points out that the volume of potential migrants is spurred by the farmers' modernization and discouraged by changes in the agrarian structure. Structural change would lessen the effect of modernization. Urban penetration played no significant role in determining potential migration.