Abstract

The current study seeks to understand the role that monetary compensation plays on the joint occurrence of imprisonment and probation for criminal traffic offenses in China. We argue that monetary compensation influences sentencing decisions primarily by manipulating the probation terms in favor of the defendant. With monetary compensation directly increasing the chances of a more lenient punishment through extended probation as opposed to more severe penalties, we have found sentence lengths for criminal traffic offenses to be concentrated at 36 months, the maximum length eligible for probation. All available sentencing documents for criminal traffic offenses from 2014 to 2016 were retrieved from the China Judgments Online website. The final dataset contains 141,689 observations. Following a joint model approach using both sentence length and probation as outcomes, we utilized a Zero-Truncated-Generalized-Inflated-Poisson model to address the distributional characteristics of sentence length, such as discrete integers, non-zero values, and the concentration of data on certain points. To avoid detecting effects of little scientific importance due to our large sample size, all results were evaluated using bootstrapping techniques. We found that the likelihood of probation increases when monetary compensation is provided, but that compensation does not make a significant difference on the sentence length for those defendants receiving less than 36 months imprisonment. When considering the concentration of sentence lengths at specific values, monetary compensation was positively associated only with the chance of inflation at the value of 36 months, and the probation itself became insignificant in predicting sentence length. The significant positive relationship between monetary compensation and lenient sentencing outcomes suggests that compensation plays a crucial role in the Chinese judicial process. Our study will not only help researchers to better understand the legal process in China, but it will also benefit the larger community as an example of utilizing new sources of data.

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