Data-Driven Insights into the Pet Industry: Market Dynamics, Trade Policies, and Sustainable Growth Strategies

Abstract

The pet industry has experienced remarkable growth over the past decade, driven by evolving consumer preferences, increased disposable income, and shifting societal attitudes toward pet ownership. This transformation is particularly evident in rapidly developing economies like China, where urbanization and an expanding middle class have accelerated the industry’s expansion. From a global perspective, North America and Europe continue to dominate the pet industry, with well-established markets and regulatory frameworks that shape industry trends. Meanwhile, emerging markets in Asia-Pacific are becoming major contributors to the industry's growth, presenting new opportunities and challenges for businesses and policymakers. To address these challenges, this study employs a combination of factor analysis, time series forecasting (ARIMA, LSTM), and policy impact assessment (Difference-in-Differences) to provide comprehensive insights into the pet industry's trajectory. Our research aims to: (1) analyze historical growth patterns and key influencing factors in China’s pet industry, (2) forecast global pet food demand using advanced predictive modeling, (3) evaluate the impact of international trade policies on China’s pet food exports, and (4) develop feasible strategies for the sustainable growth of China’s pet food industry. By integrating econometric modeling with deep learning techniques, this study bridges the gap between traditional statistical analysis and modern AI-driven market forecasting, offering valuable insights for industry practitioners and policymakers alike.