Scholars have examined how the nonprofit sector has been shaped by various environmental factors in order to predict and comprehend the role of nonprofits in modern society. However, most of the previous studies use either case studies (Burger and Veldheer 2001) or cross-sectional data (Ben-Ner and Van Hoomissen 1992; Bielefeld 2000; Grønbjerg and Paarlberg 2001) within a national boundary and there has been a paucity of research on measuring nonprofit growth using longitudinal data across countries. Therefore, findings of research are not generalizable to other countries that have different environmental contexts and measures of the nonprofit sector. In this regard, the Johns Hopkins Comparative Nonprofit Sector Project has made a significant headway in addressing the need for comparative analysis, but the project has its own limitations such as problems associated with model specifications and small sample size (22 countries in the analysis). 

Using social origin theory, this study will analyze seven years of political, economic, and socio-demographic panel data between 2006 and 2012 across 70 countries. Social origin theory contends that two primary theories of nonprofit growth—heterogeneity theory and interdependence theory—do not take political and historical roots of a country into account. As a result, the concepts and theories developed by Western societies may not successfully explain nonprofit growth in Asian countries, some of which (e.g., Korea) have maintained a strong tradition of state control over civil society. 

Nonprofit growth (our dependent variable) will be measured by “the final consumption expenditures of Nonprofit Institutions Serving Households (NPISHs) as a percentage of GDP.”

NPISHs are defined as goods and services purchased by nonprofit organizations to serve households. We will measure NPISHs as a percentage of GDP to remove the effects of natural growth of economic activity.

The independent variables include fifteen political, social and economic variables, including government effectiveness, government type, civil liberty, public welfare spending, GDP growth rate, general government total expenditures, unemployment rate, family income, population aged 65 or older, percentage of urban population, GINI index, percentage of foreign population, amount of donation, number of volunteering, and religious activity.

Panel dataset will be constructed by each country using data drawn from various sources, including World Development Indicators of World Bank, Freedom House, Legatum Institute, OECD Revenue Statistics. These data have been collected in accordance with standards established by the UN’s System of National Accounts (SNA) for data consistency across countries.

Beginning with pooled OLS, panel dataset will be filtered through fixed and random effect using hausman-test (Greene, 2008). Since this study assumes that the size and growth of nonprofits would vary across countries due to their unique political and historical roots, we expect that fixed effect model would be appropriate for the analysis. 

The findings of the data analysis would confirm effectiveness of social origin theory as a viable theory of explaining variations of nonprofit growth across countries.