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This paper presents a comprehensive analysis of the social media posts of prefectural governors in Japan during the COVID-19 pandemic. It investigates the correlation between social media activity levels, governors' characteristics, and engagement metrics. To predict citizen engagement of a specific tweet, machine learning models (MLMs) are trained using three feature sets. The first set includes variables representing profile- and tweet-related features. The second set incorporates word embeddings from three popular models, while the third set combines the first set with one of the embeddings. Additionally, seven classifiers are employed. The best-performing model utilizes the first feature set with FastText embedding and the XGBoost classifier. This study aims to collect governors' COVID-19-related tweets, analyze engagement metrics, investigate correlations with governors' characteristics, examine tweet-related features, and train MLMs for prediction. This paper's main contributions are twofold. Firstly, it offers an analysis of social media engagement by prefectural governors during the COVID-19 pandemic, shedding light on their communication strategies and citizen engagement outcomes. Secondly, it explores the effectiveness of MLMs and word embeddings in predicting tweet engagement, providing practical implications for policymakers in crisis communication. The findings emphasize the importance of social media engagement for effective governance and provide insights into factors influencing citizen engagement. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jmateco.2006.05.007 Byline: Takashi Kamihigashi (a)(b) Keywords: Stochastic growth; Unbounded utility; Bounded or unbounded shocks; Markov processes; Existence and stability of a invariant distribution Abstract: This paper studies a one-sector stochastic optimal growth model with i.i.d. productivity shocks in which utility is allowed to be bounded or unbounded, the shocks are allowed to be bounded or unbounded, and the production function is not required to satisfy the Inada conditions at zero and infinity. Our main results are three-fold. First, we confirm the Euler equation as well as the existence of a continuous optimal policy function under a minimal set of assumptions. Second, we establish the existence of an invariant distribution under quite general assumptions. Third, we show that the density of optimal output converges to a unique invariant density independently of initial output under the assumption that the shock distribution has a density whose support is an interval, bounded or unbounded. In addition, we provide existence and stability results for general one-dimensional Markov processes. Author Affiliation: (a) RIEB, Kobe University, 2-1 Rokkodai, Nada, Kobe 657-8501, Japan (b) CERMSEM, Centre d'Economie de la Sorbonne, 106-112 Boulevard de l'HA[acute accent]pital, 75647 Paris, France Article History: Received 1 October 2005; Revised 29 May 2006; Accepted 30 May 2006

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jet.2005.06.007 Byline: Takashi Kamihigashi (a), Santanu Roy (b) Abstract: This paper analyzes the nature of economic dynamics in a one-sector optimal growth model in which the technology is generally nonconvex, nondifferentiable, and discontinuous. The model also allows for irreversible investment and unbounded growth. We develop various tools to overcome the technical difficulties posed by the generality of the model. We provide sufficient conditions for optimal paths to be bounded, to converge to zero, to be bounded away from zero, and to grow unboundedly. We also show that under certain conditions, if the discount factor is close to 1, any optimal path from a given initial capital stock converges to a small neighborhood of the golden rule capital stock, at which sustainable consumption is maximized. If it is maximized at infinity, then as the discount factor approaches 1, any optimal path either grows unboundedly or converges to an arbitrarily large capital stock. Author Affiliation: (a) RIEB, Kobe University, Rokkodai, Nada, Kobe 657-8501, Japan (b) Department of Economics, Southern Methodist University, Dallas, Texas 75275, USA Article History: Received 9 January 2004; Revised 21 June 2005

To optimize stochastic models with bounded or constant-relative-risk-aversion (CRRA), a standard transversality condition (STVC) is required. In case of non-logarithmic CRRA utility, STVC is essential as long as the lifespan utility is finite at the optimum.

The stochastic versions of Michel's necessity result, a generalization of the TVC results of Weitzman and Ekeland and Scheinkman, and Kamihigashi's result, which is useful particularly in the case of homogeneous returns, is discussed. These stochastic extensions are established for an extremely general stochastic reduced-form model that assumes neither differentiability nor continuity.