Special Issue “Actuarial and Financial Risks in Life Insurance, Pensions and Household Finance”

A mid-1960s proposal to create a National Data Center has long been recognized as a turning point in the history of privacy and surveillance. This article shows that the story of the center also demonstrates how bureaucrats and researchers interested in managing the American economy came to value personal data stored as “data doubles,” especially the cards and files generated to represent individuals within the Social Security bureaucracy. The article argues that the United States welfare state, modeled after corporate life insurance, created vast databanks of data doubles that later became attractive to economic researchers and government planners. This story can be understood as helping to usher in our present age of personal data, one in which data doubles have become not only commodities, but the basis for a new capitalism. This essay is part of a special issue entitled Histories of Data and the Database edited by Soraya de Chadarevian and Theodore M. Porter.

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Editorial for Special Issue “Finance, Financial Risk Management and their Applications”

International Journal of Financial Studies ◽

10.3390/ijfs6040083 ◽

2018 ◽

Vol 6 (4) ◽

pp. 83

Author(s):

Keyword(s):

Risk Management ◽

Financial Risk ◽

Financial Risks ◽

Special Issue ◽

Financial Risk Management

We are pleased to announce the Special Issue on the Finance, Financial Risk Management and their Applications in the International Journal of Financial Studies. This Special Issue collects papers pertaining to several lines of research related to finance and financial risks. This Guest Editor’s note synthesizes the contributing authors’ propositions and findings regarding these developments and hopes that new areas can be opened for future researches.

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The Macroeconomics of Corporate Debt

The Review of Corporate Finance Studies ◽

10.1093/rcfs/cfaa015 ◽

2020 ◽

Vol 9 (3) ◽

pp. 656-665 ◽

Cited By ~ 3

Author(s):

Markus Brunnermeier ◽

Arvind Krishnamurthy

Keyword(s):

Corporate Finance ◽

Empirical Work ◽

Household Finance ◽

Important Research ◽

Special Issue ◽

Corporate Financing ◽

Editorial Decision ◽

The 2008 Financial Crisis ◽

New Research ◽

Macroeconomic Implications

Abstract The 2020 COVID-19 crisis can spur research on firms’ corporate finance decisions and their macroeconomic implications, similar to the wave of important research on banking and household finance triggered by the 2008 financial crisis. What are the relevant corporate finance mechanisms in this crisis? Modeling dynamics and timing considerations are likely important, as is integrating corporate financing considerations into modern quantifiable macroeconomics models. Recent empirical work, including articles in this special issue, on the drag from debt in the COVID-19 crisis provides a first glimpse into the new research agenda. (JEL E22, E44, G32, G33) Received July 23, 2020; editorial decision: July 23, 2020 by Editor Andrew Ellul

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Special issue on household finance: Preface

Review of Finance ◽

10.1093/rof/rfr033 ◽

2011 ◽

Vol 15 (4) ◽

pp. v-vii ◽

Cited By ~ 1

Author(s):

M. Haliassos ◽

T. Jappelli ◽

M. Pagano ◽

J. Zechner

Keyword(s):

Household Finance ◽

Special Issue

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Decomposing Dynamic Risks into Risk Components

Management Science ◽

10.1287/mnsc.2019.3522 ◽

2020 ◽

Vol 66 (12) ◽

pp. 5738-5756

Author(s):

Katja Schilling ◽

Daniel Bauer ◽

Marcus C. Christiansen ◽

Alexander Kling

Keyword(s):

Risk Management ◽

Product Design ◽

Life Insurance ◽

Stochastic Models ◽

Representation Theorem ◽

Financial Risks ◽

Systematic Analysis ◽

Martingale Representation ◽

Martingale Representation Theorem ◽

A Company

The decomposition of dynamic risks a company faces into components associated with various sources of risk, such as financial risks, aggregate economic risks, or industry-specific risk drivers, is of significant relevance in view of risk management and product design, particularly in (life) insurance. Nevertheless, although several decomposition approaches have been proposed, no systematic analysis is available. This paper closes this gap in literature by introducing properties for meaningful risk decompositions and demonstrating that proposed approaches violate at least one of these properties. As an alternative, we propose a novel martingale representation theorem (MRT) decomposition that relies on martingale representation and show that it satisfies all of the properties. We discuss its calculation and present detailed examples illustrating its applicability. This paper was accepted by Baris Ata, stochastic models and simulation.

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Effect of air pollution on household insurance purchases. Evidence from China household finance survey data

PLoS ONE ◽

10.1371/journal.pone.0242282 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242282

Author(s):

Wenxia Zhao

Keyword(s):

Air Pollution ◽

Health Insurance ◽

Life Insurance ◽

Poisson Regression ◽

Regression Models ◽

Household Finance ◽

Economic Effects ◽

Using Data ◽

The Impact ◽

Degree Of Heterogeneity

In recent years, the health and economic effects of air pollution have attracted considerable attention, and health and insurance services have been closely related to residents’ welfare. However, there are few studies on the influence of pollution on household purchases of insurance. Using data from the 2013 and 2015 China Household Finance Surveys, this study investigates the effect of air pollution on insurance purchases using Logit and Poisson regression models. It is found that air pollution significantly increases the probability of household insurance purchases and the level of premium expenditure, although the impact of air pollution on insurance purchases shows a degree of heterogeneity. Health insurance is more sensitive to air pollution than life insurance and other types of insurance. In areas where NO2 and O3 are the main types of pollutants, air pollution has a greater impact on household insurance purchases.

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