Replication Data for: Conceptual and Measurement Issues in Assessing Democratic Backsliding
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/OHXMKG
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资源简介:
This paper addresses three interrelated questions. First, how strong is the evidence that democracy has declined globally over the last decade? Second, how should we best measure (change in) democracy? Third, is there evidence that expert coders have become harsher judges of democratic quality in recent years? We begin our analysis by discussing how to conceptualize democracy and democratic backsliding. Next, focusing on V-Dem's methodology, we show---both through theoretical considerations and empirical tests---that it is highly unlikely that time-varying coder biases drive the recent observed global democratic decline. We then dissect the distinction between "subjective" and "objective" measures, examine how measurement error can affect even seemingly objective indicators, and highlight how subjectivity pervades all measurement enterprises. Finally, we evaluate Little and Meng's (2023) proposed objective democracy measures. We demonstrate multiple issues that make their measurement strategy ill-suited to study trends in global democracy or to serve as a benchmark for very different democracy measures, such as those from V-Dem.
提供机构:
Harvard Dataverse
创建时间:
2023-08-22



