RELATIONSHIP BETWEEN INFORMATION DEMAND AND MACROECONOMIC VARIABLES

RELATIONSHIP BETWEEN INFORMATION DEMAND AND MACROECONOMIC VARIABLES

Introduction

Macroeconomics is a branch of economics that deals with the behavior, performance structure and decision making process of an economy. This is a field that involves a lot of uncertainties. This fact necessitates the demand for information. In addition the reaction after receiving information is key in dealing with uncertainties in the field. This reaction, to an extent is affected by the level of uncertainties. The paper, Demand for information, Macroeconomic uncertainties and the response of the U.S Treasury security to news, gives an overview of the issues found in this field, Benamar et al, (2018). It explains the demand for information prior to nonfarm payroll announcements. Nonfarm payrolls refer to a compiled name for goods, construction and manufacturing companies in the United States. The department of labor releases an economic indicator every month as a comprehensive report on the state of the labor market. The reaction to information is very important in the macroeconomic field to mitigate the risks that are posed by large uncertainties.

Body

The paper begins by providing evidence of how investors demand more information before macroeconomic announcements are made. This is mainly when the effect of the announcements on prices is more uncertain compared to the consistency with rational models of demand for information. It is seen that information demand and price reaction are positively related to macroeconomic uncertainty. That is, the price reaction after the announcement is made is more defined when the demand for information is high. The measurement of investor’s demand is done by assessing the number of clicks on internet links referring to news about the announcements. The paper is based on data provided by Bitly. It focuses on clicks on links referring to news about nonfarm payrolls. The reason behind analysis of nonfarm payrolls is that they have the highest impact on U.S Treasury yields according to the authors. The data used is for payroll releases from 2011 to 2016. The authors believe that their data only allows them to measure demand for information just shortly before the nonfarm payroll announcements are made. This may make it impossible to explain the findings by reverse causality a drawback which can be corrected by using Bayesian learning models.

The benchmark for this paper is the response of the United States Treasure note futures to nonfarm payroll announcements. It starts by confirming from other studies that U.S Treasury futures actually respond strongly to surprises in nonfarm payroll announcements. The time to response is seen to vary significantly. It is this analysis that sets a benchmark for the assessment of the explanatory power of the author’s proxy for demand of information before the announcements are made. The estimation of the response time is done by analyzing data on U.S Treasury notes obtained from Reuters Tick History. It focuses on Treasury note futures contracts issued on three- month duration between the months of March and December.  They give focus on the front month futures contract on two-year, five-year and ten-year Treasury notes. A formula is thereby provided from which estimation can be made. After comparison of the standard deviations, it is noted that the longer sample periods have the most variation in the variables. This is as expected in contrast with that for shorter sample periods which have less variation. The findings on this analysis are in line with the Bayesian learning models which show that, high uncertainty about the value of the assets is associated with a higher impact of nonfarm payroll surprises on U.S Treasury prices.

The paper further discusses the role of the demand of information prior to nonfarm payroll announcements. This is presented as novel empirical finding. The presentation takes two forms; the strong positive association between the strength of the response of Treasury prices to nonfarm payroll announcements and the demand for information before the announcements. It is shown that there is actually a very strong positive relationship between nonfarm payroll Bitly clicks and Treasury price reactions to surprises in nonfarm payroll announcements. It is shown that the relationship occurs in line with results from a model in which investors react to greater uncertainty about macroeconomic variables. Additional tests on the predictions from the model are carried out. The model used checks whether the demand for information increases with macroeconomic uncertainty. The results show that actually there is a positive correlation between the strength of treasury price reactions to surprises in nonfarm announcements and information demand which shows that information demand is high when macroeconomic uncertainty is high. The paper is concluded by making several comments on the relationship between information demand and macroeconomic variables. It suggests that greater demand for information affects price reaction both before and after news arrival. It further ascertains that macroeconomic news release might be used to assess variations in market players perception of economic uncertainty.

Conclusion

The ability to respond to news and the reaction to prices cannot be separated. The United States can be given credit for its response to the same. Slow response would mean slow reaction to prices and would expose an economy to financial risks if this differs significantly from other economies involved in transactions with it. Generally this paper has given a clear picture of the level of relationship between the demand of information and macroeconomics variables. It has clearly demonstrated how the U.S Treasury responds to the news concerning macroeconomic variables.

Works cited

Benamar, Hedi, Thierry Foucault, and Clara Vega. “Demand for Information, Macroeconomic      Uncertainty, and the Response of US Treasury Securities to News.” (2018).