This paper studies the allocative efficiency in a Moscarini （2005）-type equilibrium search environment with learning. It is shown that the stationary equilib- rium is efficient if and only if the Hosios condition ho...This paper studies the allocative efficiency in a Moscarini （2005）-type equilibrium search environment with learning. It is shown that the stationary equilib- rium is efficient if and only if the Hosios condition holds no matter whether learning is about finn-specific human capital or about general human capital. However, the stationary equilibrium can never be efficient if externalities exist from unemployment. In contrast, even with externalities, the stationary equilibrium can be efficient under some modified Hosios condition if there is no uncertainty （standard Mortensen and Pissarides （1994）-type equilibrium search environment）. The key intuition is that the equilibrium can only be efficient if firm-worker matching is formed and terminated efficiently.展开更多
Unlike consumers in the mall or supermarkets, online consumers are “intangible” and their purchasing behaviors are affected by multiple factors, including product pricing, promotion and discounts, quality of product...Unlike consumers in the mall or supermarkets, online consumers are “intangible” and their purchasing behaviors are affected by multiple factors, including product pricing, promotion and discounts, quality of products and brands, and the platforms where they search for the product. In this research, I study the relationship between product sales and consumer characteristics, the relationship between product sales and product qualities, demand curve analysis, and the search friction effect for different platforms. I utilized data from a randomized field experiment involving more than 400 thousand customers and 30 thousand products on JD.com, one of the world’s largest online retailing platforms. There are two focuses of the research: 1) how different consumer characteristics affect sales;2) how to set price and possible search friction for different channels. I find that JD plus membership, education level and age have no significant relationship with product sales, and higher user level leads to higher sales. Sales are highly skewed, with very high numbers of products sold making up only a small percentage of the total. Consumers living in more industrialized cities have more purchasing power. Women and singles lead to higher spending. Also, the better the product performs, the more it sells. Moderate pricing can increase product sales. Based on the research results of search volume in different channels, it is suggested that it is better to focus on app sales. By knowing the results, producers can adjust target consumers for different products and do target advertisements in order to maximize the sales. Also, an appropriate price for a product is also crucial to a seller. By the way, knowing the search friction of different channels can help producers to rearrange platform layout so that search friction can be reduced and more potential deals may be made.展开更多
文摘This paper studies the allocative efficiency in a Moscarini （2005）-type equilibrium search environment with learning. It is shown that the stationary equilib- rium is efficient if and only if the Hosios condition holds no matter whether learning is about finn-specific human capital or about general human capital. However, the stationary equilibrium can never be efficient if externalities exist from unemployment. In contrast, even with externalities, the stationary equilibrium can be efficient under some modified Hosios condition if there is no uncertainty （standard Mortensen and Pissarides （1994）-type equilibrium search environment）. The key intuition is that the equilibrium can only be efficient if firm-worker matching is formed and terminated efficiently.
文摘Unlike consumers in the mall or supermarkets, online consumers are “intangible” and their purchasing behaviors are affected by multiple factors, including product pricing, promotion and discounts, quality of products and brands, and the platforms where they search for the product. In this research, I study the relationship between product sales and consumer characteristics, the relationship between product sales and product qualities, demand curve analysis, and the search friction effect for different platforms. I utilized data from a randomized field experiment involving more than 400 thousand customers and 30 thousand products on JD.com, one of the world’s largest online retailing platforms. There are two focuses of the research: 1) how different consumer characteristics affect sales;2) how to set price and possible search friction for different channels. I find that JD plus membership, education level and age have no significant relationship with product sales, and higher user level leads to higher sales. Sales are highly skewed, with very high numbers of products sold making up only a small percentage of the total. Consumers living in more industrialized cities have more purchasing power. Women and singles lead to higher spending. Also, the better the product performs, the more it sells. Moderate pricing can increase product sales. Based on the research results of search volume in different channels, it is suggested that it is better to focus on app sales. By knowing the results, producers can adjust target consumers for different products and do target advertisements in order to maximize the sales. Also, an appropriate price for a product is also crucial to a seller. By the way, knowing the search friction of different channels can help producers to rearrange platform layout so that search friction can be reduced and more potential deals may be made.
