Economic Assessment of Weather Service: Evidence from Taiwanese Household Sector

This study examines the economic valuation of public weather information services in Taiwan by quantifying household willingness to pay (WTP) through the Contingent Valuation Method (CVM). Utilizing a large-scale nationally representative survey (N=12,429), we implement Multiple Imputation (MI) to rigorously address the high proportion of protest responses (57.3%), thereby mitigating selection bias and recovering the latent economic valuation of the household sector. The empirical findings identify a unique “Participation–Intensity Divergence” in weather service valuation. While residents in metropolitan areas exhibit a significantly lower probability of entering the payment market, reflecting a higher “participation hurdle” that is likely driven by elevated public-good expectations and information substitutes, their latent valuation intensity is significantly higher than that of non-metropolitan residents once the participation threshold is crossed. The analysis confirms that perceived utility, service satisfaction, and income positively influence WTP, while age demonstrates a negative correlation. Under a conservative baseline (non-protest sample), the monthly WTP is NT$39.55 for metropolitan and NT$34.48 for nonmetropolitan households, representing an annual realizable value of NT$2.53 billion – 2.94 billion and NT$0.98 billion – 1.13 billion, respectively. Furthermore, addressing protest responses via Multiple Imputation reveals a latent value, with adjusted monthly WTP of NT$35.6 for metropolitan and NT$31.27 for non-metropolitan areas, corresponding to potential annual values of NT$5.37 billion – 6.11 billion and NT$2.09 billion – 2.38 billion, respectively. These results underpin a dual-track strategy: lowering psychological entry barriers in urban centers while enhancing sector-specific applications in weather-sensitive regions. This research offers both a methodological benchmark for addressing protest bias and a theoretical framework for understanding complex demand structures in rapidly urbanizing environments.