论文标题
以商品价格的随机趋势估算竞争性存储模型
Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices
论文作者
论文摘要
我们为商品价格提出了一个州空间模型（SSM），将竞争性存储模型与随机趋势相结合。这种方法符合存储决策的经济合理性，并增加了存储模型的先前确定性趋势规范。使用粒子马尔可夫链蒙特卡洛程序估算参数。在四个商品市场上的经验应用表明，随机趋势SSM比确定性趋势规范受到青睐。随机趋势SSM标识了与确定性趋势规范不同的结构参数。特别是，在随机趋势SSM下，需求的估计价格弹性明显更大。
We propose a state-space model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of storage decisions, and adds to previous deterministic trend specifications of the storage model. Parameters are estimated using a particle Markov chain Monte Carlo procedure. Empirical application to four commodity markets shows that the stochastic trend SSM is favored over deterministic trend specifications. The stochastic trend SSM identifies structural parameters that differ from those for deterministic trend specifications. In particular, the estimated price elasticities of demand are significantly larger under the stochastic trend SSM.
