McKinsey & Company

About: McKinsey & Company is a company organization based out in New York, New York, United States. It is known for research contribution in the topics: Supply chain & Population. The organization has 928 authors who have published 1061 publications receiving 55959 citations.

Differences Between Tight and Loose Cultures: A 33-Nation Study

Abstract: With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ecological and historical threats (e.g., high population density, resource scarcity, a history of territorial conflict, and disease and environmental threats), broad versus narrow socialization in societal institutions (e.g., autocracy, media regulations), the strength of everyday recurring situations, and micro-level psychological affordances (e.g., prevention self-guides, high regulatory strength, need for structure). This research advances knowledge that can foster cross-cultural understanding in a world of increasing global interdependence and has implications for modeling cultural change.

Net Gain: Expanding Markets through Virtual Communities

Abstract: What are virtual communities? How do they operate? How can they help expand markets, increase visibility, and improve profitability? What effects have they had on business models and marketing strategies? John Hagel discussed these issues in his keynote speech at the Direct Marketing Association's 1998 net.marketing Conference held April 1998.

The Association Between Income and Life Expectancy in the United States, 2001-2014

Abstract: Importance The relationship between income and life expectancy is well established but remains poorly understood. Objectives To measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation. Design and Setting Income data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy. Exposure Pretax household earnings as a measure of income. Main Outcomes and Measures Relationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas. Results The sample consisted of 1 408 287 218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61 175 per year). There were 4 114 380 deaths among men (mortality rate, 596.3 per 100 000) and 2 694 808 deaths among women (mortality rate, 375.1 per 100 000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% ( P r = −0.69, P r = 0.72, P r = 0.42, P r = 0.57, P Conclusions and Relevance In the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.

Liberalization, Moral Hazard in Banking, and Prudential Regulation: Are Capital Requirements Enough?

Abstract: In a dynamic model of moral hazard, competition can undermine prudent bank behavior. While capital-requirement regulation can induce prudent behavior, the policy yields Pareto-inefficient outcomes. Capital requirements reduce gambling incentives by putting bank equity at risk. However, they also have a perverse effect of harming banks' franchise values, thus encouraging gambling. Pareto-efficient outcomes can be achieved by adding deposit-rate controls as a regulatory instrument, since they facilitate prudent investment by increasing franchise values. Even if deposit-rate ceilings are not binding on the equilibrium path, they may be useful in deterring gambling off the equilibrium path.