The Unassuming Economist

From an article by Daron Acemoglu:

“Artificial intelligence is reshaping the world in front of our eyes. The concerns around AI, however, extend beyond the uncertainty and disruption that accompany any other radical technological change. They stem in part from the direction AI development has taken: many leading companies are engaged in a single-minded pursuit of artificial general intelligence (AGI).

AGI is generally understood as an AI system that can match or exceed human capabilities on most economically valuable tasks. In such a world, the automation of work would not be limited to specific industries or routine jobs. Instead, machines would take over many forms of work, including highly skilled professions. The consequences of this displacement of human labour would be unparalleled.

To draw attention to this urgent public-policy challenge, I joined thousands of economists and AI researchers in signing We Must Act Now, a statement urging policymakers and technology leaders to steer AI towards complementing, rather than replacing, human labour.”

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From a paper by Mark Zandi, Cristian deRitis, Marisa DiNatale, Dante DeAntonio, Matt Colyar, Shandor Whitcher, Justin Begley, Ilir Hysa, and Gwen Semmens:

“Artificial intelligence stands to become one of the most consequential technologies in generations, if not in the history of humankind, with enormous implications for the economy. However, the specifics of how it will shape the future remain highly uncertain and are the subject of immense debate. Many technologists deeply involved in AI’s development believe it will massively increase productivity, resulting in significant net job loss and much higher unemployment. Conversely, most economists who look to the economic history of past general-purpose technologies tend to be more circumspect, expecting AI to lift productivity but also to diffuse slowly enough through the economy for the job market to adjust more gracefully. There may be bouts of higher unemployment, but any increase will be modest, as jobs lost to AI will be largely offset by new jobs supported by the income and wealth it creates.”

From a paper by Marina da Silva Sanches:

“This study examines the effects of fiscal consolidation on income inequality in OECD countries from 1978 to 2014, using narrative data. Employing local projections methodology and using a Gini decomposition interpretation, we estimate the impact of austerity episodes on disposable income, market income, wage, and functional inequalities. While the literature has primarily focused on the overall effect of fiscal consolidation on disposable income inequality, this paper examines how different dimensions of inequality respond to fiscal consolidation episodes. We find an increase in wage inequality in the short and medium runs, and a decrease in labor’s share of income in the short run. The results also underscore the importance of social protection in the short term. Additionally, we observe a significant increase in earnings inequality, when including the lower end of the distribution. Finally, spending-based austerity measures are, in general, more relevant than tax-based ones. Results are robust to several tests.”

From a paper by Marina da Silva Sanches:

“This study examines the effects of fiscal consolidation on income inequality in OECD countries from 1978 to 2014, using narrative data. Employing local projections methodology and using a Gini decomposition interpretation, we estimate the impact of austerity episodes on disposable income, market income, wage, and functional inequalities. While the literature has primarily focused on the overall effect of fiscal consolidation on disposable income inequality, this paper examines how different dimensions of inequality respond to fiscal consolidation episodes. We find an increase in wage inequality in the short and medium runs, and a decrease in labor’s share of income in the short run. The results also underscore the importance of social protection in the short term. Additionally, we observe a significant increase in earnings inequality, when including the lower end of the distribution. Finally, spending-based austerity measures are, in general, more relevant than tax-based ones. Results are robust to several tests.”

From a paper by Debkumar Chakrabarti, Sankalpa Bhattacharjee, Pradeepta Sethi:

“This paper undertakes a comprehensive review of some of the less-discussed factors that harbor the potential to explain the wide variations in structural transformation, especially amongst developing economies. We begin by critically reviewing the effects of income, relative price, and international trade, which are generally considered drivers of structural change, with special emphasis on developing economies. Subsequently, we bring to the forefront three comparatively less-discussed factors—income inequality, financial market imperfections, and government policy that can explain a large part of the divergences in the transformation patterns of developing economies. Underscoring the limitation of the conventional discourse that relates cross-country differences in structure in terms of cross-country differences in manufacturing, we emphasize the need for the theoretical discourse to move beyond the industry-centric approach to focus on the recent research that views the surge of services as an additional engine of growth and the possible avenues through which it can affect structural transformation.”