A Study On Price Stickiness And Price Setting In China Based On Big Data

Microeconomic behavior of prices and its implications for macroeconomic models is one of the most challenging themes in the field of monetary policy analysis. If there exists nominal price stickiness in the market, then after the economy suffered the impact of economic fluctuations, the market cannot quickly clearing and the monetary policies implemented by monetary authorities can affect real output of goods and services. Therefore, the nominal price stickiness assumption has almost become the starting point for all modern macroeconomic theory models. Using web text extraction and data mining technology, this paper scraped prices information from well-known online shopping platform to build a product-level, high frequency data set to provide empirical insights on the measurement of price stickiness, the price-setting rules, price stickiness causes and the effects of price stickiness under open conditions, and discussed the macro implications of research findings.Firstly, this paper discussed a fundamental question that is almost overlooked so far:Are nominal prices in Chinese retail market sticky? How to estimate the degree of stickiness of nominal prices? Although many researchers have used micro data to conduct measurement of price stickiness for their own country in recent years, trying to provide microscopic evidence for the construction of macroeconomic models, but there is not have the empirical study to estimate the nominal price stickiness based on micro data from Chinese retail markets. The fourth chapter of this paper using a new data source-the scraped prices from the Internet, to estimate the degree of nominal price stickiness in Chinese retail market for the first time. The results show that:(1) compared with developed countries, the degree of price stickiness in China is at a low level, with a weighted median price change frequency of 1.23% per day. The median implied duration of price is about 2.7 months with sales and 3.4 months without sales. (2)The price stickiness is highly heterogeneous across groups, providing a possible explanation for the differences between the micro and macro stickiness. (3) We find no evidence to support the hypothesis of downward nominal rigidity. (4) The degree of price stickiness in eastern and central regions is relatively close and was higher than that of the western region. The price of imported goods is more flexible as well as top 20 goods according to the sales ranking.Secondly, as the most basic DSGE model assumptions, price setting rules is critical for the structure macro model accurately portray a country’s economic situation. Many Literatures constructed New Keynesian DSGE Model to analyze China’s economic fluctuations, monetary and fiscal policy and other issues, these studies generally assume sticky prices and price changes of products using a fixed ratio adjustment rules, and cited the probability of price adjustments of the United States as parameters to calibrate the model. Due to the different market conditions in each country, theoretical models directly draw foreign conclusions lack the appropriate factual basis, to a certain extent, affected the reliability of the findings of these studies. This reality requires empirical evidence based on micro data to support a reasonable set of macro models of China. In view of this, the fifth chapter, using micro-level data from the Internet, to estimate the distribution of magnitude of price adjustments, exploring firms follow time-dependent rules or state-dependent rules. The results show that the distribution of the size of price changes is bimodal, consistent with predictions of State-Dependent Pricing model. The intensive margin accounts for 64% of inflation’s variance, indicating that magnitude of price changes is the main source of inflation in China and the price-setting rules is indeed primarily associated with the state.Thirdly, from the perspective of traditional Chinese culture, this paper discusses the causes of Chinese retail market price stickiness. Specifically, Chapter VI constructed a product-level data set of more than 400 million observations to examine the existence of price point model on China’s market and its impact on price stickiness. The results show that, unlike Western countries, there is obvious lucky number phenomenon in China’s retail markets, where the most favored price point is 8, while number 4 is avoided; according to the Markov transfer dynamic analysis results, the price point of 8 is most stable, it is highly probable that the price-ending without 8 in the current period is like to be changed to that with 8 in the following period; Based on Logit model, the empirical results show that the price point of 8 has a significantly positive impact on price stickiness, meaning that "lucky prices" have strong stickiness. During holiday seasons, retailers are more concerned about avoiding unlucky numbers, which further indicates the impact of cultural background on price stickiness. This study provides new empirical evidence regarding the sources of price stickiness.Finally, using more than 160,000 kinds of imported goods information from "etao", Chapter VII constructed the product-level panel data set to study exchange rate pass-through (ERPT) on imported consumer goods and to explore the possible impact of price stickiness on the exchange rate of incomplete pass. We find exchange rate pass-through on imported consumer goods to be 37.5% in the short-run and approximately 42%-46% in the long-run. We also find that pass-through to food and industrial goods price is close and was greater than that of services, whether in the short-run or long-run. We further empirically document, that on average goods imported from Vietnam, Philippines, Thailand and other emerging countries have a pass-through that is at least twice as high as that of EU, U.S., Japan and other developed countries, which means the need to adopt a differentiated policy to deal with the problem of trade imbalance.