Who Was Zvi Griliches?

Zvi Griliches was an empirical economist who taught at the University of Chicago and Harvard University. His work revolved around statistical analysis techniques that would provide more accurate measures of economic concepts.

Key Takeaways

  • Zvi Griliches was an economist at the University of Chicago and Harvard University.
  • Griliches' work focuses on empirical applications of economics and econometrics to questions around technology, economic growth, education, and human capital.
  • He was known for his emphasis on the collection and use of high quality data and statistical estimation techniques.

Understanding Zvi Griliches

Zvi Griliches was born in Kaunas, Lithuania, in 1930. During the Second World War, he survived the concentration camp at Dachau. After liberation, he taught himself English in a British internment camp and eventually went on to serve in the Israeli army before earning a PhD in economics from the University of Chicago. Griliches taught at the University of Chicago between 1964 and 1969, where he received the John Bates Clark Medal of the American Economic Association. In 1969, Griliches joined the faculty of Harvard University, where he served as president of the American Economic Association and the Econometric Society.

Late in his life, Griliches took up the study of numismatics, in part due to his genealogical studies which turned up ancestors who worked at the St. Petersburg Mint in the late 19th and early 20th centuries. This study produced an article which appeared in the Journal of the Russian Numismatic Society in 1998.

Griliches succumbed to pancreatic cancer in 1999.

Contributions

Many of the advancements pioneered by Zvi Griliches came in the field of econometrics, which applies statistical modeling to data in order to test economic hypotheses.

Technological Diffusion and Economic Growth

Griliches' doctoral dissertation followed the spread of hybrid corn in American markets, demonstrating a link between spending on research and development and national economic gain. Later researchers were able to generalize these concepts to demonstrate links between economic factors and the development of new technology. Griliches' work directed attention to the microeconomics of technology adoption and the impact of technology adoption on productivity in various industries and sectors of the economy.

Returns to Education

The economic benefit of education was a major theme of Griliches' research during the 1970s. His work focused on measuring the impact that schooling had on earnings relative to other variables, especially the effect of innate or otherwise independent individual ability. Based on the data and statistical evidence available, he argued that natural ability likely does not significantly bias research that shows positive impact of education on earnings. This tends to support human capital formation theories of education rather than pure a pure job market signaling function for education.  

Hedonic Pricing

In the process of his work on inflation with the Stigler Commission in the 1960s, Griliches co-developed a technique called hedonics to provide a more accurate measure of the importance of economic variables to the value of goods and services and the measurement of productivity. Hedonic pricing and regression models are still widely used in calculating and adjusting price indexes and are popular as pricing tools in real estate markets. 

Data and Statistics

Griliches' time at the University of Chicago coincided with a revolution in the study of economic statistics brought about by advances in computing technology. His research improved the basis for measuring many economic phenomena. The field of econometrics makes heavy use of complex statistical and mathematical tools, including regression analysis, time series methods, frequency distributions, and a range of probability-related techniques. Griliches worked to improve the measurement and collection of the data and statistics that could be used for empirical research.

Griliches' work benefited greatly and contributed to the use and spread of large computerized datasets in economics. The need to crunch the huge amount of data necessary to prove or disprove economic hypotheses requires enough computing power that it has spawned a series of software designed specifically to deal with sophisticated econometric modeling.