The epidemiology of corporate PAC formation, 1975–1984

Substantial political power is often attributed to interest groups. The origin of this power is not quite clear, though, and the mechanisms by which influence is effectuated are not yet fully understood. The last two decades have yielded a vast number of studies which use empirical models to assess the importance of interest groups for the formation of public policy. Each of these studies yields insights on particular, confined aspects of interest group politics. To get a more complete picture of the results, however, a broad survey of the literature seems useful. It is the purpose of this paper to provide such a survey.JEL classification: D72; D78

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“…Grier et al, , 1994Humphries, 1991 ;Kennelly and Murrell, 1991 ;McKeown, 1994;Pittman, 1976Pittman, , 1977Pittman, , 1988and Zardkoohi, 1985).…”

Section: Stakes and Collective Actionmentioning

confidence: 99%

Interest groups: A survey of empirical models that try to assess their influence

Potters

Sloof

1996

European Journal of Political Economy

214

113

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“…That is, it seems unlikely that a common set of variables would influence each of these choices in the same manner. Here, of course, we return to the collective action hypothesis that has been used to explain all three choices: engaging in lobbying , establishing a PAC (Andres 1985;Masters and Keim 1985;Humphries 1991;McKeown 1994;Roberts 1991,1994), and raising and allocating PAC funds (Boies 1989;Grier, Munger, and Roberts 1994;Conybeare and Squire 1994). How important are collective action issues for each of these choices?…”

Section: A New Interpretation Of Political Action Committee Formationmentioning

confidence: 99%

“…Foremost among these hypotheses, of course, are those drawn from Olson's (1965) analysis of collective action. The result is the small but quite active literature on the formation of PACs (Andres 1985;Masters and Keim 1985;Boies 1989;Humphries 1991;McKeown 1994;Roberts 1991, 1994;Conybeare and Squire 1994). As Cigler (1991, 113) pointed out, however, the rapid melding of existing theories with new sources of data does not always lead to correct answers, especially when it leads scholars to mischaracterize the questions.…”

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confidence: 99%

Reconceptualizing Pac Formation

Gray

Lowery

1997

American Politics Quarterly

125

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After criticizing current models of political action committee (PAC) formation as flawed both in the samples used in tests and in the specifications tested, we develop a new explanation of PAC formation that emphasizes competition for access among those already engaged in lobbying. We test both organization-and state-level implications of this alternative account, respectively, employing survey and aggregate data on PACs in the American states. The empirical findings provide preliminary support for our explanation and sharply contradict prior evidence that PAC formation is governed by problems of free riding.If Cohen, March, and Olson (1972) applied their &dquo;garbage can&dquo; model of organizations to political science research, they might start by noting several cans holding, respectively, a variety of data sets, the concepts and hypotheses discussed in the literature, and a number of scholars in need of publishing. The temporal sorting of material in the three garbage cans would then be used to explain why certain research

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“…Event history models predicting the timing of an action or event from characteristics of the person's or organization's network position have frequently been used although it should be noted that the network position sometimes merely represents whether one is married or the number of children one has. The impact of the size and composition of a person's social network on health or mortality is a popular topic (Adams et al 2002;Bygren et al 1996;Gustafsson et al 1998;Kang and Bloom 1993;Litwin and ShiovitzEzra 2006;Patterson et al 1996;Payette et al 2000;Samuelsson and Dehlin 1993;Trovato 1998;Villingshoj et al 2006) and so is the impact of exposure to adopters of an innovation through social or geographical network ties (Bogart 2007;Bohman 2006;Chaves 1996;Davis and Stout 1992;Edling and Sandell 2001;Lipp and Krempel 2001;McKeown 1994;Mintrom and Vergari 1998;Soule 1997;Strang 1991;Strang and Tuma 1993;Van den Bulte and Lillien 2001). The relevance of network ties for the hazard of finding a job has also been studied (Bernasco et al 1998;Brandt 2006;Yakubovich and Kozina 2000) as well as the hazard of leaving a field or organization (Clarysse et al 1996;McPherson et al 1992;Mossholder et al 2005;Sutton and Chaves 2004).…”

Section: Event History Models Applied To Social Networkmentioning

confidence: 99%

Networks of action and events over time. A multilevel discrete-time event history model for longitudinal network data

Nooy

2011

Social Networks

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Longitudinal network data recording the moment at which ties appear, change, or disappear are increasingly available. Event history models can be used to analyze the dynamics of time-stamped network data. This paper adapts the discrete-time event history model to social network data. A discrete-time event history model can easily incorporate a multilevel design and time-varying covariates. A multilevel design is needed to account for dependencies among ties and vertices, which should not be ignored in a small longitudinal network. Time-varying covariates are required to analyze network effects, that is, the impact of previous ties. In addition, a discrete-time event history model handles constraints on who can act or who can be acted upon in a straightforward way. The model can be estimated with multilevel logistic regression analysis, which is illustrated by an application to book reviews, so network evolution can be analyzed with a fairly standard statistical tool.Keywords: network dynamics; discrete-time event history models; multilevel logistic regression analysis; longitudinal social networks; book reviewing.In the analysis of longitudinal social networks, relatively little attention has been paid to the timing of relational events, namely the moments at which ties appear, change, or disappear. Initially, this kind of data was not available because longitudinal data were collected by means of repeatedly administered surveys (Katz and Proctor 1959: 318; Runger and Wasserman 1979: 144). As a consequence, models for network dynamics

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The epidemiology of corporate PAC formation, 1975–1984

Cited by 29 publications

References 17 publications

Interest groups: A survey of empirical models that try to assess their influence

Interest groups: A survey of empirical models that try to assess their influence

Reconceptualizing Pac Formation

Networks of action and events over time. A multilevel discrete-time event history model for longitudinal network data

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