Equitable GrowthでWill McGrewという研究員が「How job-matching technologies can build a fairer and more efficient U.S. labor market」という論説を書き、本ブログで4年前に紹介したジョン・クイギンの議論に触れている。

Despite its widespread impact, the search and matching model has faced criticism for failing to fully account for several empirical phenomena in contemporary labor markets, notably the cyclicality and persistence of vacancies, unemployment, and job creation, as well as the persistence of inflation in response to monetary shocks. As economist John Quiggin of the University of Queensland explains, one of the key criticisms of the search and matching theory has focused on its failure to accurately predict the effects of the internet on unemployment. Since the dominant framework models unemployment as a function of search and matching frictions, unemployment should have declined with the rise of the internet, which increased the information available to both employers and employees. Yet this empirical prediction did not materialize. Indeed, over the past two decades, despite sustained innovations involving the internet, unemployment spiked twice—in the early 2000s, after the dot-com bust and again in the Great Recession beginning in December 2007. In the latter case, the spike was particularly durable, as unemployment has only recently returned to healthy levels.


While these empirical critiques call into question the implications of the job search and matching model for key macroeconomic labor market variables, this model may nevertheless be helpful for understanding the internal dynamics of the job search process itself—and particularly the role of technological innovation in this process. Indeed, the centrality of transaction costs in terms of search and matching in the mainstream model is a logical frame in which to analyze the effects of technological innovations, which presumably have the capacity to reduce various types of frictions.

サーチ&マッチングモデルはマクロは説明できないがミクロは説明できる、という話だが、実は4年前にも、同じEquitable Growthの別の研究員(Marshall Steinbaum)が同様のことを述べている*1

Quiggin also argues that the big question in labor market macroeconomics—essentially, why is labor demand low and why does it stay low—can only be answered by macroeconomic models. He asserts that search-and-matching models don’t add any insight. Let me offer an alternative schematization. There are two big questions in business cycle macroeconomics. Why do recessions happen? And why do they look the way they look, with high, persistent unemployment and a cascade of other symptoms of illness in the labor market?
Search-and-matching models don’t do anything on the first question; one has to assume the recession into the story. But the model goes a long way toward answering the second one if you allow for factual wage-bargaining and other modifications. In short, the model is a great tool to have in the economist’s toolbox, provided it’s used skillfully and with attention to the data, first and foremost.
クイギンはまた、なぜ労働需要が低調で、なぜ低調のままなのか、という労働市場マクロ経済学における大きな問題は、マクロ経済モデルによってのみ回答できる、と論じている。彼は、サーチ&マッチングモデルは何ら洞察を付け加えない、と主張している。ここで別の見方をしてみよう。景気循環マクロ経済学では2つの大きな問題がある。なぜ景気後退が起きるのか? そしてなぜ景気後退はあのように高く持続的な失業率と、その他様々な労働市場の弊害を伴うのか?


Instead of discarding this model, a future research agenda should build on it while incorporating important structural frictions in the contemporary U.S. labor market, notably monopsony (or the dominance of a small number of employers), occupational segregation (the disproportionate concentration of women and ethnic minorities in certain fields), and labor market polarization (the recent increase in low-skill, low-wage and high-skill, high-wage jobs at the expense of middle-class employment). Including both structural and informational frictions in the Mortensen-Burdett model also sheds light on points of intervention where innovators and policymakers can help facilitate a more efficient and more equitable job search and matching process. For example, in Alan Manning’s book, Monopsony in Motion, the economist describes how lack of information, among other frictions, is pronounced when there are too few employers in a single labor market, underlying the importance of public intervention to prevent labor market concentration.
このモデルを捨て去るのではなく、このモデルの上に構築する形で今後の研究を進めるべきである。その際、買い手独占(少数の雇用者による支配)、職業の分断(一部の分野での女性や少数民族の過度の集中)、ならびに労働市場の分極化(中流の雇用が減少する一方で低技能・低賃金と高技能・高賃金の雇用が増加したという最近の現象)に代表される現代米労働市場の重要な構造的摩擦を取り入れるべきである。モーテンセン=バーデットモデルに、構造ならびに情報の摩擦を取り込むことによっても、イノベーターと政策当局者がより効率的で公平なジョブ・サーチ&マッチング過程を実現できる介入ポイントに解明の光を当てることになるだろう。例えばアラン・マニングの著書「Monopsony in Motion*2」では、一つの労働市場での雇用者が少なすぎる場合、様々な摩擦の中でも情報の欠如が大きな意味を持つことが説明されており、労働市場の集中を防ぐ公的介入の重要性が強調されている。


At the very least, better matching technologies could help reduce informational search frictions and the related skills mismatch—with positive implications for both inequality and growth. With the goal of improving existing job boards and similar platforms as a starting point, companies—including Alphabet Inc’s Google unit and Indeed—have begun to use artificial intelligence and machine learning to narrow down the most relevant jobs for job-seekers. Indeed also uses natural language processing to help employers identify the best candidates for vacancies by analyzing language from applicants’ resumes and other submitted materials. These technologies and further innovations in this vein would enhance both the equity and efficiency of labor markets by reducing the inequality associated with skills mismatch and search frictions, driving down unemployment given shorter search times and increasing labor force participation and work hours in response to improved matching to jobs consistent with workers’ skills and interests. A report by the McKinsey Global Institute estimates that these advances could add 2 percent to global GDP in the next decade.



Monopsony In Motion: Imperfect Competition In Labor Markets

Monopsony In Motion: Imperfect Competition In Labor Markets