Economic data

About: Economic data is a research topic. Over the lifetime, 1435 publications have been published within this topic receiving 30479 citations.

Introduction to the Theory and Practice of Econometrics

Abstract: This book interweaves inferential approaches and theory and practice in econometrics. Basic statistical and linear algebra concepts are introduced as they are needed to give life to the statistical model under study. Most econometric applications start with a tentative theory or hypothesis a sample of data and the goal of learning something about the phenomena under study from the limited set of observations. Therefore a sample of data that may be used to investigate a particular economic hypothesis is presented to motivate the analysis of each of the statistical models presented. This linkage between the economic process that is thought to have generated the data and a particular statistical model is a unifying theme throughout the book. It progresses from the special case of investigating the possibilities for determining the location and scale parameters for a population from a sample of observations to investigating a complex simultaneous system of structural equations under general stochastic assumptions. To ensure that the reader understands the basic concepts and conclusions as they relate to linear statistical models simple special case models are evaluated and then the analysis is repeated for the general case. The 1st half of book gives the student a solid introduction to the formulation and use of linear statistical models. The 2nd half introduces the student to the econometric problems that arise when it is taken into account that economic data are stochastic dynamic and simultaneous and that the optimal statistical procedure sometimes changes as we change the statistical model the amount and type of information used and the measure of performance.

Expanded Trade and GDP Data

Abstract: Many sources of economic data cover only a limited set of states at any given point in time. Data are often systematically missing for some states over certain time periods. In the context of conflict studies, economic data are frequently unavailable for states involved in conflicts, undermining the ability to draw inferences of linkages between economic and political interactions. For example, simply using available data in a study of trade and conflict and disregarding observations with missing data on economic variables excludes key conflicts such as the Berlin crisis, the Korean War, the Cuban Missile Crisis, and the Gulf War from the sample. A set of procedures are presented to create additional estimates to remedy some of the coverage problems for data on gross domestic product, population, and bilateral trade flows.

Global non-linear effect of temperature on economic production

Abstract: Economic productivity is shown to peak at an annual average temperature of 13 °C and decline at high temperatures, indicating that climate change is expected to lower global incomes more than 20% by 2100. Temperature, and therefore climate change, can affect a country's economic productivity, but it has not been clear if rich and poor countries, or different aspects of economic productivity, show similar relationships. These authors use economic data from 166 countries for the years 1960 to 2010 to uncover a universal nonlinear relationship that reconciles earlier results. Economic productivity peaks at an annual average temperature of 13 °C, and the authors explore the likelihood of global economic contraction under future warming scenarios. Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies1,2, but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries3,4. In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature5, while poor countries respond only linearly5,6. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems7,8 and to anticipating the global impact of climate change9,10. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non-linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change11,12, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.

Energy and the u.s. Economy: a biophysical perspective.

Abstract: A series of hypotheses is presented about the relation of national energy use to national economic activity (both time series and cross-sectional) which offer a different perspective from standard economics for the assessment of historical and current economic events. The analysis incorporates nearly 100 years of time series data and 3 years of cross-sectional data on 87 sectors of the United States economy. Gross national product, labor productivity, and price levels are all correlated closely with various aspects of energy use, and these correlations are improved when corrections are made for energy quality. A large portion of the apparent increase in U.S. energy efficiency has been due to our ability to expand the relative use of high-quality fuels such as petroleum and electricity, and also to relative shifts in fuel use between sectors of the economy. The concept of energy return on investment is introduced as a major driving force in our economy, and data are provided which show a marked decline in energy return on investment for all our principal fuels in recent decades. Future economic growth will depend largely on the net energy yield of alternative fuel sources, and some standard economic models may need to be modified to account for the biophysical constraints on human economic activity.

Economic prediction using neural networks: the case of IBM daily stock returns

Abstract: A report is presented of some results of an ongoing project using neural-network modeling and learning techniques to search for and decode nonlinear regularities in asset price movements. The author focuses on the case of IBM common stock daily returns. Having to deal with the salient features of economic data highlights the role to be played by statistical inference and requires modifications to standard learning techniques which may prove useful in other contexts. >