Do data breach disclosure laws reduce identity theft?

In the United States, identity theft resulted in corporate and consumer losses of $56 billion dollars in 2005, with up to 35 percent of known identity thefts caused by corporate data breaches. Many states have responded by adopting data breach disclosure laws that require firms to notify consumers if their personal information has been lost or stolen. Although the laws are expected to reduce identity theft, their effect has yet to be empirically measured. We use panel data from the U.S. Federal Trade Commission to estimate the impact of data breach disclosure laws on identity theft from 2002 to 2009. We find that adoption of data breach disclosure laws reduce identity theft caused by data breaches, on average, by 6.1 percent. © 2011 by the Association for Public Policy Analysis and Management.     

Big data for policymaking: fad or fasttrack?

The buzz surrounding big data has taken shape in various theoretical and practical forms when it comes to policymaking. The paper combines current research streams with long-standing discussions on government and technology in public policy and public administration, such as e-government and evidence-based policymaking. The goal is to answer the question whether big data is a fleeting trend or has long-lasting effects on policymaking. Three larger themes in the literature are identified: First, the role that institutional capacity has within government to utilize big data analytics; second, government use of big data analytics in the context of digital public services; and finally, the way that big data information enters the policy cycle, focusing on substantive and procedural policy instruments. Examples from the education, crisis management, environmental and healthcare domain highlight the opportunities and challenges for each of these themes. Exploring the various aspects of big data and policymaking shows that big data is here to stay, but that its utilization by government will take time due to institutional barriers and capacity bottlenecks.     

What can we learn from analyzing historical data on social security entitlements?

We use data from Social Security administrative records to examine the lifetime patterns of initial entitlement to retired-worker and Disability Insurance (DI) benefits across cohorts born in different years. Breaking out age-at-entitlement patterns for different birth-year cohorts reveals close adherence in entitlement ages to changes in program rules, such as increasing the full retirement age. The proportion of a cohort that becomes newly entitled to DI benefits rises noticeably during recessions and at ages 50 and 55, and cumulative entitlement rate patterns show that more recent cohorts rely increasingly on DI benefits in their late 30s and 40s.     

Per-capita public expenditures and population size: a non-parametric analysis using French data

Based on the median voter model, we specify a flexible general framework of the effect of municipality size on per-capita public expenditures. Previous literature has recognized that municipality size should have a non-linear effect on the quality of public goods provision and to this end different papers have applied a range of alternative parametric specifications. Using a very large sample of French “communes” we are able to estimate the effect of municipality size semi-parametrically. In contrast with the parametric specifications, we find evidence of the U-shaped relationship between per-capita public expenditures and population which is predicted by theory.     

What explains the dynamics of citizens’ satisfaction with democracy? An integrated framework for panel data

Literature on political support broadly offers three micro-level models: socio-economic status, democratic process evaluations, and political performance evaluations explain people's differences in satisfaction with democracy. While tests show that these explanations complement each other, we do not know how. We combine for the first time all three models into one common longitudinal framework by explicitly considering aspects of time. We argue that relatively stable factors, such as socio-economic status, only explain general levels, whereas more time-sensitive factors, such as evaluations, explain differences between citizens at specific points in time. The results of latent growth curve modelling applied to nine-wave panel data support our general hypothesis of a common longitudinal framework. These results also show that economic evaluations play a prominent role as do some (but not all) electoral results. The findings have theoretical and methodological implications, and they offer a new perspective on the meaning of ’satisfaction with democracy’.     

Information disclosure policy: Do state data processing efforts help more than the information disclosure itself?

The Toxics Release Inventory (TRI) was expected to reduce health risks stemming from emissions of hazardous chemicals by increasing public pressure on polluters. However, raw TRI data fails to transmit accurate information fitted to the public's interest. TRI is a massive and complex data set that, in its raw form, provides information on the pounds of toxics released, rather than the risks these releases pose to human health, which is the true quantity of interest. Consequently, raw TRI data needs to be refined and interpreted in terms of health risks by its users, which requires analytical sophistication and substantial data processing. State governments have attempted to increase of the usefulness of the TRI to the general public via two types of policies: (1) selection and dissemination of raw TRI data for plants within the state, and (2) data processing activities producing more refined reports and further data analysis. This study assesses the effectiveness of those two policies, asking how much each contributes to the intended policy outcome of reducing health risks. Our results show that state‐level data dissemination efforts lowered the total number of pounds of chemicals released, but had little effect on health risks. State‐level data processing efforts, in contrast, did lead to significant reductions in health risks. We conclude that simple dissemination of the data was ineffective (and even counterproductive in some instances), and that the states' data processing efforts have played a critical role in achieving the TRI's intended policy goal by providing better information to end users. © 2010 by the Association for Public Policy Analysis and Management.     

It’s the economy, and then some: modeling the presidential vote with state panel data

Using data for the 50 US states for presidential elections from 1972 to 2004 two theories for determining state voting outcomes are considered jointly: the ‘economy matters’ and ‘home grown-ness’ theories. Fixed-effects regressions show that measures of the ‘economy matters’ (real income, unemployment and a proxy for inflation) have the predicted effects on state voting patterns for presidential elections. The home grown theory receives mixed support. There is weak evidence that incumbent-party candidates garner greater support in their home states. There is strong support, however, for the proposition that incumbent-party candidates fare worse in the home state of rival-party candidates.     

Modeling proximity and directional decisional logic: What can we learn from applying statistical learning techniques to VAA-generated data?

ABSTRACT

Voting advice applications-(VAA) generated data provide an ideal data source for testing competing theories of voting behavior. To that end, this paper focuses on comparing metrics of voter-party ideological concordance based on rival theories of issue voting (proximity and directional theory). Classification performance of the competing models, in terms of correctly predicting party choice, is evaluated in diverse cross-national settings. Drawing on the EUvox dataset (a VAA for the European Parliament elections in 2014) statistical learning techniques are used to model the decisional logic of voters in high- and low-dimensional policy space. The results show that statistical learning methods can improve classification performance significantly and that how dimensionality is modeled affects the performance of competing issue voting models.     

Does poor health cause political passivity even in a Scandinavian welfare state? Investigating the impact of self-rated health using Swedish panel data

Poor health is generally believed to cause political passivity. Prior studies that satisfactorily acknowledge the causality problems involved are mainly limited to considering turnout and the U.S.A., so we lack knowledge of how non-electoral participation is affected in other countries. This article considers Sweden, characterized by a generous welfare state and an extensive public health system. Using unique panel data, which allow more thorough analyses of causality, poor health was found to have a negative effect on voting but not on non-electoral participation. By primarily focusing on other countries than Sweden and the U.S.A., it is a task for future longitudinal research to show whether the belief that poor health lead to political passivity is incorrect—or whether Sweden is an exceptional case, due to the barriers to participation being particularly low there.     

What do we really know? The effect of reporting thresholds on inferences using environmental right‐to‐know data

Environmental right‐to‐know regulations require regulated entities to publicly disclose measures of environmental performance but exempt entities from these disclosure requirements if they manufacture, process, or use a chemical below some threshold level. Environmental right‐to‐know data are widely used to assess environmental performance by academics, regulators, non‐profit organizations, and the public. This paper uses data from Massachusetts to estimate the effect of reporting thresholds in environmental right‐to‐know programs on the validity of inferences using data from these programs. The analysis indicates that errors in inference introduced by reporting thresholds may be significant. Up to 40% of the observed decline in reported toxic releases in Massachusetts may be attributed to non‐reporting due to the reporting thresholds. In addition, quartile rankings of facilities may be in error up to 45% of the time when behavior around the reporting thresholds is not taken into account.     

Donors in transition and the future of development cooperation: What do the data from Brazil,India, China,and South Africa reveal?

How are Development Assistance Committee (DAC) donors evolving their financial flows and aid modalities in response to the growing influence and economic power of Southern BRICS? After presenting the shifting landscape of international development cooperation, we explore five hypotheses about the changing nature of DAC aid allocation patterns and modalities in BRICS countries. In our conclusion, we reflect on the evolution of DAC engagement in Brazil, China, India, and South Africa (BASIC countries) and what it might mean for all official donors. Our assessment is that the changing geopolitical environment for development cooperation is once again privileging economic diplomacy concerns within DAC donors, propelling specific kinds of decisions about the choice of instruments, sectors, and modalities in BASIC countries. It would appear that the administrative practice of foreign aid is increasingly derived from changes within the institutional environment for international development.     

If low‐income blacks are given a chance to live in white neighborhoods,will they stay? Examining mobility patterns in a quasi‐experimental program with administrative data

Abstract

After describing the distinctive features of various policy models of residential mobility, we examine the long‐term outcomes of the Gautreaux program. Administrative records provide baseline characteristics for all participants, and we located recent addresses for over 99 percent of a random sample of 1,506 participants an average of 14 years after original placement.

Although 84 percent of the families made subsequent moves, the racial composition of the current address is strongly related to program placement, even among movers, and after family attributes and premove neighborhood characteristics are controlled. Combined with our prior findings, these results suggest that residential mobility has an enduring, long‐term impact on the residential locations of these families. Contrary to models that assume that families’ enduring preferences will quickly erase these moves, these results suggest the need for further research to consider whether mobility alters preferences or structural barriers.