Conversations on Transformation

Structural Transformation and Economic Growth (STEG), led by CEPR
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The STEG Podcast Series ' Conversations on Transformation' investigates some of the most important new research in structural transformation, growth and economic development.

  1. 3d ago

    AI in the office and the factory

    Some studies find that AI destroys jobs, some find no effect, and some find that it creates them. Gustavo de Souza of the Chicago Fed argues that AI has different labour market impacts in different occupations. To test this, he uses records of Brazilian firms, who can register their software with the government for 50 years of copyright protection. The register holds a near-complete record of the AI programs written in the country. Almost half of them are for office work, but 44% are for production, on farms, in factories and on building sites. He tells Tim Phillips about the scale and direction of those different effects of AI on employment. De Souza presented the research at STEG's sixth Annual Conference in Nairobi in January 2026.  The research behind this episodede Souza, Gustavo. 2025. "AI in the Office and the Factory: Evidence from Administrative Software Registry Data." Working Paper 2025-11, Federal Reserve Bank of Chicago. Revised 2026. To cite this episodePhillips, Tim, and Gustavo de Souza. 2026. "AI in the office and the factory." Conversations on Transformation (podcast). About the guestGustavo de Souza is an Economist in the economic research department of the Federal Reserve Bank of Chicago. He holds a PhD in Economics from the University of Chicago. His research spans macroeconomics, labour economics, development and public finance. The views in his paper and in this episode are his own, and do not necessarily reflect those of the Federal Reserve Bank of Chicago or the Federal Reserve System. Research cited in this episodeAI as a prediction technology is the idea at the centre of de Souza's argument. Ajay Agrawal, Joshua Gans and Avi Goldfarb set it out in "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction" (Journal of Economic Perspectives, 2019). AI uses large amounts of data to predict something: which post a social media user will click on, whether a bank transfer is fraud, or which word comes next in a sentence. If a worker's main task is to make predictions, AI can replace them. If a worker makes decisions with the help of predictions, AI can make them more productive. Studies that find AI reduces jobs include Michael Webb's "The Impact of Artificial Intelligence on the Labor Market" (2020), one of the first papers to measure which occupations are exposed to AI, and Xiang Hui, Oren Reshef and Luofeng Zhou's "The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market" (Organization Science, 2024), which found that freelancers lost work after generative AI tools became available. Studies that find little or no effect include Anders Humlum and Emilie Vestergaard's "Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI" (NBER Working Paper 33777, 2025), first circulated as "Large Language Models, Small Labor Market Effects". It uses Danish data on workers who use AI chatbots, and finds no meaningful effect on earnings or hours. Daron Acemoglu, David Autor, Jonathon Hazell and Pascual Restrepo, in "Artificial Intelligence and Jobs: Evidence from Online Vacancies" (Journal of Labor Economics, 2022), found that firms that adopt AI hire fewer people for other roles, but found no effect on employment in occupations or industries as a whole. Studies that find AI increases jobs look at firms that adopt it. Menaka Hampole, Dimitris Papanikolaou, Lawrence Schmidt and Bryan Seegmiller, in "Artificial Intelligence and the Labor Market" (NBER Working Paper 33509, 2025), use resume data and find that at firms that adopt AI, productivity gains outweigh the jobs it displaces. Philippe Aghion and co-authors, in "How Different Uses of AI Shape Labor Demand: Evidence from France" (AEA Papers and Proceedings, 2025), find that the effect depends on how firms use AI. Tania Babina, Anastassia Fedyk, Alex He and James Hodson, in "Artificial Intelligence, Firm Growth, and Product Innovation" (Journal of Financial Economics, 2024), find that firms that invest in AI grow faster. Experiments with AI assistants often find that less experienced and less skilled workers gain the most. In "Generative AI at Work" (Quarterly Journal of Economics, 2025), Erik Brynjolfsson, Danielle Li and Lindsey Raymond studied customer support agents who were given an AI assistant. Productivity rose most for new and low-skilled agents. De Souza finds the same pattern in Brazilian factories. Brazil's software register is kept by the National Institute of Industrial Property (Instituto Nacional da Propriedade Industrial, INPI). A law of 1987 gave 50 years of copyright protection to software registered there. To register, a firm gives the name of the program, the names of its programmers, where it will be used, the methods and programming languages it uses, and a short description. The source code stays confidential. Registration is cheap and gives legal proof of ownership, so it has become standard practice. De Souza collected every registered program that uses AI and linked it to RAIS, Brazil's administrative records of all formal jobs, from 2003 to 2022. Brazil's informatics policy explains why the register exists. In 1984, the military government passed the National Informatics Policy to build a domestic computer industry, with restrictions on imports and support for local firms. Civilian rule returned in 1985, and the software law followed two years later. Today little software in Brazil is imported, so the register captures most of the software that Brazilian firms use. Manufacturing execution systems are the software that controls and tracks a production line: stock, output forecasts, workstations and quality. They account for nearly 40% of the AI programs for production in the register. One firm in the data, Techplus, has registered an industrial copilot: a chatbot with access to the manuals of a factory's machines, connected to live data from the production line, so that workers can ask it how to operate equipment and diagnose faults. The second most common use is quality control, in which computer vision checks products for defects as they leave the line. Measuring exposure to AI follows a method that Webb developed. De Souza compares the text of each occupation's task descriptions with the descriptions of AI programs in the register. The more similar the two, the more exposed the occupation is to AI. The instrument deals with the risk that software firms aim AI at occupations that are already growing or shrinking for other reasons. When a programming language becomes more popular in the United States, its community grows, along with its libraries and online answers, and software in that language becomes cheaper to write in Brazil too. De Souza measures popularity with the Tiobe index, and links languages to types of software with posts on Stack Overflow, the question and answer site for programmers. COBOL, created in the 1950s, still runs much of the world's banking; a Reuters estimate cited in the paper puts its share of in-person transactions at more than 80%. But it is no longer taught and its community is small, so AI for banking is expensive to build. R, created in the 1990s for statistics, has a large and growing community, so AI for data analysis is cheap. A bank teller is therefore less exposed to AI than an archivist, for reasons that have nothing to do with the Brazilian labour market. The missing intercept problem is why de Souza is cautious about the effect on the whole economy. His method compares occupations that are more exposed to AI with occupations that are less exposed. It can show that one group gains relative to the other, but not whether employment rose for everyone, fell for everyone, or rose for some and fell for others. His comparisons between regions, which are not in the paper, suggest that AI increases total employment and moves workers between occupations. More Conversations on Transformation episodesBroadband on the factory floor. Gaurav Chiplunkar finds that when Colombian manufacturing plants got broadband, they hired more production workers, not managers or technical staff. Digital technologies in developing countries. Robert Townsend asks whether digital tools can do the work of the social structures that support trade and credit in poor economies. Further readingFrom Skills to Occupations: Comparative Advantage and Cross-Country Income Differences, a STEG working paper by Charles Gottlieb, Jan Grobovsek and Alexander Monge-Naranjo, uses data from 50 countries to show how workers sort into occupations, and how technology that favours skilled workers widens the income gap between rich and poor countries. Mobile Internet Adoption and Inclusive Structural Change: Evidence from Nigerian Non-Farming Enterprises, a STEG working paper by Bernardo Caldarola, finds that mobile internet made small Nigerian firms more productive, mostly in services, but did not create new firms.

    AI in the office and the factory

  2. Oct 22

    Tracking Kenya's tractors

    A tractor can plough an acre of Kenyan maize land in about an hour and a half. By hand, it takes a farmer nearly a week. Few smallholders can afford to buy a tractor, so they rent one. The tractor’s owner often lives in town, and employs an operator to drive the tractor to the fields and do business. To minimise risk, the owner keeps their tractor close to home, even when the best work is far away. Sophie Nottmeyer studied what changed when owners could observe exactly where the tractor was. She used GPS records from about 1,200 tractors fitted with a tracking app from the start-up Hello Tractor, covering close to a million fields, and satellite images of the land they worked. As owners learned to use the app, their tractors travelled further, finding better business opportunities. A year after adoption, they worked about 55 km further from home than in their first month. Nottmeyer presented the research at STEG's sixth Annual Conference in Nairobi in January 2026. She tells Tim Phillips what satellites reveal about the fields the tractors reached, and why a fuel subsidy that did the same job would cost hundreds of times more. The research behind this episodeNottmeyer, Sophie. 2025. "Trac(k)tors of Change: Monitoring, Tractor Mobility and Agricultural Mechanization in Kenya." Working paper, November 2025. A summary is available as a STEG policy brief: "Following the tracks: how digital monitoring expands access to agricultural mechanisation across space" (2026). To cite this episodePhillips, Tim, and Sophie Nottmeyer. 2026. "Tracking Kenya's tractors." Conversations on Transformation (podcast). About the guestSophie Nottmeyer is a Research Economist in the Directorate General of Economic Research at Banco de Mexico. She was previously a Postdoctoral Researcher at Universitat Pompeu Fabra in Barcelona, and holds a PhD in Economics from CEMFI in Madrid. Her research spans market access, organisational frictions and informal institutions, and how they interact with geography and climate. She has also worked with remote-sensing scientists to estimate maize yields in Kenya from satellite data. Research cited in this episodeHello Tractor is an agricultural technology company based in Nairobi. In 2018 it introduced a GPS tracking device for tractors, fitted by a mechanic, with a mobile and web app that shows owners where their tractor is in real time. The app reports how many jobs the tractor did, how many acres it worked, how long it ran and how far it drove, and it can replay the tractor's exact path across a field. In 2023 owners paid US$125 to install the device and US$60 a year to use the app. Nottmeyer's data cover every job done by tractors that adopted it between 2018 and 2025, about 917,000 in total. Moral hazard arises when one party cannot observe what another does on its behalf. Kenyan tractor owners hire operators, who are often paid from the revenue they collect. Because the owner cannot see how many acres were ploughed, an operator can under-report jobs, take unauthorised work or use fuel for other purposes. Owners respond with surprise visits, fuel checks and rules that the tractor must come home every night. All of these work only if the tractor stays nearby. The problem is sharper because many owners are not farmers at all; according to Kenya's 2019 census, 33% of tractor owners live in cities. Misallocation describes an economy in which capital or labour does not go where it would produce the most. Chang-Tai Hsieh and Peter Klenow showed in "Misallocation and Manufacturing TFP in China and India" (Quarterly Journal of Economics, 2009) how large the cost of such gaps can be. Nottmeyer measures misallocation as the spread in the returns that tractors earn in different places. If a tractor would earn more in a distant district than near home, but never goes there, the economy loses output. Counting Kenya's tractors is harder than it sounds. No official source records tractor ownership or use, Kenya's last nationwide agricultural census was in 1979, and the Food and Agriculture Organization stopped publishing its global series on agricultural machinery in 2009. The roughly 1,225 tractors in Nottmeyer's data represent between 1.73% of the tractors counted by the 2019 census and 8.75% of the last FAO figure, from 2008. Comparing each tractor with itself is how Nottmeyer deals with the lack of a control group. The data begin only when a tractor adopts the app, so she uses each tractor's first month as its baseline, on the assumption that owners take time to trust the information and change how they manage operators. The average distance from home was 70 km in that first month. It rose by about 30 km after six months, 55 km after one year and 112 km after two years. The pattern is similar for early and late adopters, for older tractors whose owners had run them before fitting the device, and for tractors that return home every night. Nottmeyer does not claim these estimates are strictly causal, but the alternative explanations she tests do not account for the pattern. Satellite measures of crop growth stand in for yields, which nobody records at field level in Kenya. Nottmeyer uses Sentinel-2 images from the European Union's Copernicus programme to calculate the Normalized Difference Vegetation Index (NDVI), which measures how green and dense vegetation is. Ploughing leaves a field bare at the start of the season, so the gap between the lowest and highest NDVI in a year captures both land preparation and crop growth. She matches 33,256 fields worked by monitored tractors with similar fields nearby. In the year of the visit, the gap rises by about 0.4 standard deviations more in the visited fields, and part of the gain persists in later years. Because some of the comparison fields may also have been ploughed by other tractors, this is a lower bound on what mechanisation does. A spatial model of tractor location turns these results into national figures. Owners choose where to send a tractor by weighing the returns in each place against the cost of distance, and monitoring lowers that cost. When all Hello Tractor tractors behave as if they had five years of experience with the app, the spread of returns across places falls by 15.9% and total output rises by 2.18%, compared with tractors that have just adopted it. If every tractor in Kenya had the technology, output would rise by 1.3%. A fuel subsidy is the obvious alternative policy, because it makes long trips cheaper. Nottmeyer calculates that to achieve the same gains, a subsidy would have to cover almost all the fuel a tractor uses per kilometre, at a total cost of about US$9.33 billion. Fitting all 70,930 tractors in the 2019 census with the device and a five-year subscription would cost about US$30.1 million. Monitoring in other industries follows the same logic wherever an owner hands a vehicle to someone else to operate. Thomas Hubbard's "The Demand for Monitoring Technologies: The Case of Trucking" (Quarterly Journal of Economics, 2000) studied the onboard computers that US trucking firms installed to track drivers. Erin Kelley, Gregory Lane and David Schonholzer ran an experiment with Nairobi's minibus owners, reported in "Monitoring in Small Firms: Experimental Evidence from Kenyan Public Transit" (American Economic Review, 2024), and found that tracking devices helped owners manage drivers and raised profits. More Conversations on Transformation episodesMoving to profitability. Carolyn Pelnik asks why street vendors and motorcycle taxi drivers in Kampala stay in less profitable parts of the city, another case in which mobile workers and assets do not go where they would earn most. Slack and economic development. Felix Samy Soliman explains why firms in Kenya leave labour and capital idle, and how much growth that unused capacity could deliver. Further readingMisallocation and Product Choice, a STEG working paper by Stepan Gordeev and Sudhir Singh, uses farm and crop data from India to estimate how much output is lost when inputs are spread unevenly between farms, and shows that the answer depends on which crops farmers can choose to grow. Tillers of Prosperity: Land Ownership, Reallocation, and Structural Transformation, a STEG working paper by Shuhei Kitamura, finds that when the land reform enforced by the Allies after the Second World War gave tenants ownership of their farms, they adopted low-cost farm technology, relied less on family labour, and more young people left for the cities.

    Tracking Kenya's tractors

  3. Oct 15

    Is electricity a weak link in development?

    In many cities in low-income countries, the grid fails often enough that businesses keep a diesel generator out the back. So an unreliable electricity grid looks like it is holding poor economies back. In many countries, lenders are putting money behind that idea. But Martin Shu and his co-authors, Jonathan Colmer and David Lagakos, set out to test it. They assembled data on power plants, fuel, workers and imported generators in 89 countries, and measured how productive each electricity sector was. In the poorest countries, electricity was about three-quarters as productive as in the US — in other words, much closer to the frontier than their economies. And in the economic model they built using their data, bringing every country up to the world frontier adds only about 1% to long-run GDP. Shu presented the research at STEG's sixth Annual Conference in Nairobi in January 2026. He tells Tim Phillips where the productivity gap in electricity lies, why a shoe factory that is better at left shoes than right shoes explains the small gains, and which part of the economy is the real bottleneck. The research behind this episodeColmer, Jonathan, David Lagakos, and Martin Shu. 2026. "Is the Electricity Sector a Weak Link in Development?" Working paper, January 2026 version presented at the STEG Annual Conference, Nairobi. An earlier version appeared as NBER Working Paper 32041 (2024). To cite this episodePhillips, Tim, and Martin Shu. 2026. "Is electricity a weak link in development?" Conversations on Transformation (podcast). About the guestMartin Shu is Assistant Professor of Economics at the School of Management and Economics and the Shenzhen Finance Institute of the Chinese University of Hong Kong, Shenzhen. His research spans macroeconomics, development and labour economics, including what household and firm data reveal about structural transformation, and why children in poor countries are more likely to follow their parents into the same occupation. He holds a PhD in Economics from Boston University and bachelor's and master's degrees from the Hong Kong University of Science and Technology. Research cited in this episodeWeak links are sectors whose problems hold back the whole economy. When inputs are strong complements, output depends heavily on the least productive link in the chain, so a small sector can matter far more than its size suggests. The idea draws on Albert Hirschman's The Strategy of Economic Development (1958), and Charles Jones formalised it in "Intermediate Goods and Weak Links in the Theory of Economic Development" (American Economic Journal: Macroeconomics, 2011), which uses electricity as a motivating example. Shu and his co-authors ask whether electricity fits that description in poor countries today. Total factor productivity (TFP) measures how much output an economy or a sector gets from its inputs. If two countries have the same capital and the same number of workers, but one produces more, it has higher TFP. Shu measures each country against the United States. The figures for whole economies come from the Penn World Table, hosted by the Groningen Growth and Development Centre and described by Robert Feenstra, Robert Inklaar and Marcel Timmer in "The Next Generation of the Penn World Table" (American Economic Review, 2015). The paper uses version 9.1; the current release, PWT 11.0, is supported by STEG. Agriculture's productivity gap is the comparison Shu uses to show why measuring TFP is not enough. Farming in poor countries is far less productive than the rest of the economy, as Francesco Caselli ("Accounting for Cross-Country Income Differences," Handbook of Economic Growth, 2005) and Diego Restuccia, Dennis Tao Yang and Xiaodong Zhu ("Agriculture and Aggregate Productivity: A Quantitative Cross-Country Analysis," Journal of Monetary Economics, 2008) document. Farmers are also the majority of workers in many developing countries. Yet few economists call agriculture a weak link. Whether a sector is a bottleneck depends on how it connects to the rest of the economy, and answering that needs a model as well as data. The electricity data combine several sources. Generating capacity comes from S&P Global Platts' World Electric Power Plants database, which lists more than 200,000 plants; the authors use generating capacity alone because it tracks transmission and distribution capacity closely. Power output and fuel use come from the International Energy Agency, and employment from national statistics offices. To count power from private generators, the authors use imports of generators recorded in the UN Comtrade database, an approach inspired by Francesco Caselli and Daniel Wilson ("Importing Technology," Journal of Monetary Economics, 2004). It works because few poor countries make their own generators. On the authors' conservative measure, generators supply about 7.6% of capacity on average. Labour's share of revenue in electricity is about 7%, in rich and poor countries alike. The authors collected annual reports, financial statements and SEC filings for 69 privately owned electricity companies in 31 countries, choosing private firms because their decisions follow profit rather than government mandate. Labour's share shows no relationship with GDP per capita. A share that does not change with income points to a Cobb-Douglas production function, in which each input's share of costs stays constant, and that simplifies the TFP calculation. Transmission and distribution losses are power that leaves a plant but never reaches a customer, lost as heat in wires and transformers, or stolen. According to IEA data, they average 14% of output across the sample, 22% in the poorest quarter of countries and 7% in the richest. They are the strongest predictor of low electricity TFP; once they are taken into account, the link between electricity TFP and national income largely disappears. Shu points to upgraded transformers close to end users, and ultra-high-voltage transmission lines, as the investments that would close the gap. Complementarity describes inputs that work together and cannot easily replace each other, like left and right shoes. The model sets the elasticity of substitution between electricity and everything else at 0.2, following Ernst Berndt and David Wood ("Technology, Prices, and the Derived Demand for Energy," Review of Economics and Statistics, 1975). Strong complementarity sounds as if it should make electricity more important. Shu's shoe factory shows why it does not: when a sector is already efficient, making it more efficient frees few resources, and output still waits on the less productive partner. Hulten's theorem, from Charles Hulten's "Growth Accounting with Intermediate Inputs" (Review of Economic Studies, 1978), predicts the economy-wide gain from a productivity improvement in one sector: multiply the improvement by the sector's Domar weight, its sales as a share of GDP. The authors treat any gain above that prediction as the sign of a weak link. Raising electricity TFP to the world frontier, defined as the 90th percentile, means an average increase of 43%, and by Hulten's rule it would add 1.7% to GDP. The model delivers about 1%, and only six countries beat the benchmark. The biggest exceptions are Ethiopia and Kenya, where frequent outages make power expensive or halt production. The authors also test their results against David Baqaee and Hannes Malmberg's "Long-Run Comparative Statics" (NBER Working Paper 33504, 2025), which extends Hulten's approach to allow for capital accumulation. Raising productivity outside electricity is the counterpart experiment. When the authors raise TFP in the rest of the economy by the same proportion instead, every country gains more than Hulten's theorem predicts, and the capital stock grows by 75% on average. Shu's conclusion is about balance. With complementary sectors, pushing one to an extreme achieves little, and today it is the non-electricity sector that lags. More Conversations on Transformation episodesA Microeconomic Perspective on Misallocation. Eric Verhoogen explains how economists diagnose the wedges that keep resources from their best use, the same kind of distortion Shu's model uses to capture outages and costly self-generated power. Structural change in sub-Saharan Africa. Gaaitzen de Vries and Kei-Mu Yi ask whether African economies follow the familiar path of structural transformation, a wider view of the sectors that Shu argues are holding growth back. Further readingCan Mass Electrification (Still) Cause Structural Change?, a STEG synthesis paper by Eric Hsu and Mitchell VanVuren, reviews the mixed evidence on whether connecting people to power still raises productivity and incomes in low- and middle-income countries, as it appears to have done in the past. Under the Grid: Price and Informational Barriers to Grid Densification in Benin, a STEG working paper by Arnaud Dakpogan, Megan Lang and Alpha Ly, finds that a connection subsidy did not raise formal connection rates on average, but information on costs and procedures nearly doubled them among households with no connection at all.

    Is electricity a weak link in development?

  4. Oct 8

    Broadband on the factory floor

    In 2010, fast broadband in Colombia reached Bogota. Then the government began to lay fibre to hundreds more municipalities. Factories in those towns gained the tools city firms already had: a website, online orders, job ads, video calls, bank transfers in seconds. Would it grow firms, and would it take jobs? Gaurav Chiplunkar (University of Virginia) followed about 12,000 Colombian manufacturing plants from 2008 to 2019 to find out. The firms that got broadband grew, but not in the way the conventional wisdom predicted. They hired more people for the production line and bought more machines, but they hired no more managers or technical staff. The larger firms appear to have grown fastest.  Chiplunkar presented the research at STEG's sixth Annual Conference in Nairobi in January 2026. He tells Tim Phillips how he separated the effect of broadband from everything else happening in Colombia's economy, why rising wages both helped and held back the firms that adopted it, and what the changes in Colombia can tell us about AI. The research behind this episodeChiplunkar, Gaurav. 2026. "General Purpose Technology and Firm Production: Evidence from Internet Adoption." Working paper, presented at the STEG Annual Conference, Nairobi, January 2026. Draft available from the author on request. To cite this episodePhillips, Tim, and Gaurav Chiplunkar. 2026. "Broadband on the factory floor." Conversations on Transformation (podcast).About the guestGaurav Chiplunkar is Assistant Professor of Business Administration in the Global Economies and Markets area at the University of Virginia's Darden School of Business, which he joined in 2019. His research spans labour market frictions, the barriers women and young people face in work and entrepreneurship, industrial policy, and how digital technologies reshape firms and jobs. He holds a BA in Economics from Delhi University, an MSc from the London School of Economics, an MPhil from the University of Cambridge and a PhD in Economics from Yale University. He is a research affiliate of BREAD, J-PAL, the International Growth Centre, IZA and Y-RISE. Research cited in this episodeGeneral purpose technologies are innovations that spread across the whole economy, improve over time and make further innovation possible. Timothy Bresnahan and Manuel Trajtenberg gave the idea its name in "General Purpose Technologies: 'Engines of Growth'?" (Journal of Econometrics, 1995). Electricity is the classic example; the internet and AI are the recent ones. Chiplunkar's point is that such a technology does not remove one barrier but several at once. It opens markets, cheapens inputs and changes how a firm organises itself, and studies that measure one channel at a time can miss how the channels interact. Mobile phones and Kerala's fish markets are the subject of Robert Jensen's paper "The Digital Provide: Information (Technology), Market Performance, and Welfare in the South Indian Fisheries Sector" (Quarterly Journal of Economics, 2007). When mobile phone coverage spread along the Kerala coast between 1997 and 2001, fishermen could check prices before they chose where to land their catch. Price differences between beach markets collapsed and waste disappeared. Chiplunkar cites it as the clearest picture of what better information does to markets in a low-income economy. Vive Digital and the National Fibre Optic Project supplied the rollout that Chiplunkar studies. Colombia's ICT ministry, MinTIC, made the Proyecto Nacional de Fibra Óptica the backbone of its Vive Digital plan. The contract, awarded in November 2011, committed the operator to connect 788 municipalities to the fibre network, chosen mainly for coverage and for the technical feasibility of laying cable. Because the fibre reached different towns at different times, otherwise similar firms gained access to broadband in different years. The Annual Manufacturing Survey (Encuesta Anual Manufacturera, or EAM) is run by DANE, Colombia's national statistics agency. Chiplunkar uses a panel of about 12,000 formal manufacturing establishments. It records production and inputs, with separate counts of managers, professional and technical staff, and production workers. A module on information technology asks firms whether they have a website, sell online, take orders online, hire online or use internet calls. That module shows what firms did with broadband, not only whether they grew. Informal firms are not in the survey; Chiplunkar plans to study them next. Shift-share instruments deal with a basic problem: the towns that got fibre, and the firms that adopted broadband first, were not chosen at random. Chiplunkar combines two sources of variation, how fast the number of broadband providers grew in a region and how heavily a firm's industry already relied on the internet. A consumer electronics maker and a rubber tyre maker in the same town face the same new supply of broadband, but the electronics firm has far more to gain. Comparing them removes anything that affects the whole town; comparing electronics firms across towns removes anything that affects the whole industry. The approach draws on work by Kirill Borusyak, Peter Hull and Xavier Jaravel, including "Quasi-Experimental Shift-Share Research Designs" (Review of Economic Studies, 2022). Skill-biased and scale-biased technical change frame the jobs question. In the 1990s and 2000s, economists asked whether computers and the internet would raise demand for highly skilled workers and push out the less skilled. A scale-biased change instead lets firms grow by doing more of what they already do. Colombia's factories fit the second pattern; they added production workers and machines, not managers or technical staff. Chiplunkar cautions that the survey records job categories, not skills, so treating production work as less skilled is an approximation. General equilibrium effects are the consequences that come back to firms once the whole economy adjusts. When broadband raises wages, workers spend more, which lifts demand for firms' products. But firms must also pay their workers more, which makes them hire fewer. In Chiplunkar's preliminary estimates, higher incomes explain about a quarter of the gain in firms' sales, while higher wages cut the gain in labour use by about a fifth. In the results he presented in Nairobi, broadband raised Colombia's manufacturing output by 7% and real incomes by 1.5%. More Conversations on Transformation episodesDigital technologies in developing countries. Robert Townsend asks how digital tools such as blockchain can reproduce, and sometimes improve on, the social structures that support trade in rural Thailand, a different view of what technology lets firms do. A Microeconomic Perspective on Misallocation. Eric Verhoogen explains why the most productive firms in low-income countries often stay small. Chiplunkar finds that broadband helped the larger firms grow fastest. Further readingMobile Internet, Collateral and Banking, a STEG working paper by Angelo D'Andrea, Kangni Kpodar, Nicola Limodio, Andrea Presbitero and Patrick Hitayezu, finds that 3G coverage in Rwanda moved borrowers from microfinance to commercial banks on better terms, partly because it helped them obtain land titles under a land reform and use them as collateral. Technology Adoption and Late Industrialization, a STEG working paper by Jaedo Choi and Younghun Shim, uses historical data on South Korean firms' contracts to adopt foreign technology after the war and finds productivity gains for adopters and spillovers to nearby firms.

    Broadband on the factory floor

  5. Oct 1

    Moving to profitability

    Kampala's street vendors and boda boda drivers own little that ties them to one spot. The fruit seller has a wheelbarrow. Yet a vendor in a parish near the top of the city's profit ladder earns more than three times as much as a similar vendor near the bottom. Two-thirds of them believe they could earn more somewhere else. So why do they stay put? Carolyn Pelnik (World Bank) asked them, and in this episode of Conversations on Transformation, she tells Tim Phillips what she discovered.  Most said they did not have the cash to move. So she ran an experiment with 2,883 entrepreneurs. Some were paid a subsidy to work at least three kilometres from their usual pitch. Others got the same money with no conditions. Some got a card naming parishes where businesses like theirs earned more. Only those who got both cash and information earned more, and while the payments lasted their profits rose by 45%. But, when the payments stopped, most went back to their lives as before. Why? Based on research presented at STEG's sixth Annual Conference in Nairobi in January 2026.  The research behind this episodePelnik, Carolyn. 2025. "Moving to Profitability? Alleviating Constraints on Microentrepreneur Location." Working paper, July 2025. An earlier version was published as a PEDL Working Paper in November 2024. Presented at the STEG Annual Conference, Nairobi, January 2026. To cite this episodePhillips, Tim, and Carolyn Pelnik. 2026. "Moving to profitability." Conversations on Transformation (podcast). About the guestCarolyn Pelnik is a research economist in the Prosperity Research Program of the World Bank's Development Research Group. She received her PhD in Economics and Public Policy from Tufts University in 2025, and holds a BS and an MPP from the University of Virginia. Her research spans small and micro enterprises, market access, access to financial services, poverty traps, land markets, and urban economics in low- and middle-income countries. An earlier version of the paper discussed in this episode won the Northeastern Universities Development Consortium (NEUDC) Distinguished Paper Award in 2024. The views she expresses in this episode are her own, and not necessarily those of the World Bank. Research cited in this episodeSpatial equilibrium and compensating differentials set the benchmark Pelnik tests against. In a world without frictions, entrepreneurs crowd into the most profitable places until competition erodes the gap. Where a gap persists, one classic explanation, developed by Sherwin Rosen (1979) and Jennifer Roback (1982), is that the extra money compensates for something unpleasant about the place, such as congestion or pollution. If Pelnik's payments only compensated entrepreneurs for an unpleasant move, they would have returned home the day the money stopped. A week later, most had not. Conditional and unconditional cash transfers let the experiment separate two stories. The conditional transfer paid only entrepreneurs who moved at least three kilometres; the unconditional transfer paid the same amount with no strings attached. If entrepreneurs want to move but cannot afford to, both should produce similar moves. If they would rather not move at all, only the conditional payment should. For the entrepreneurs who responded to the information, the two transfers worked in almost exactly the same way. The coefficient of variation is the standard deviation of a set of values divided by their mean. It lets researchers compare how risky places are when their average profits differ. Pelnik finds that it rises in Kampala's more profitable parishes; the best places to trade are also the least predictable. Testing for consumption smoothing follows Robert Townsend's 1994 paper "Risk and Insurance in Village India," published in Econometrica. If a household is well insured, its spending should not rise and fall with its own day-to-day income. Pelnik finds that either form of cash weakens the link between an entrepreneur's daily profit and their spending, consistent with the payments acting as a floor that made a risky move bearable. Selection into credit markets is the parallel Pelnik draws for policy. Lori Beaman, Dean Karlan, Bram Thuysbaert, and Christopher Udry, in "Selection into Credit Markets: Evidence from Agriculture in Mali" (Econometrica, 2023), show that the farmers who choose to borrow are not a random draw, and that who takes up a loan shapes what a lending programme achieves. In Kampala, adding information changed who took up the moving subsidy. Pelnik suggests that bundling information with credit might similarly steer loans to the entrepreneurs who stand to gain most. More Conversations on Transformation episodesThe returns to migration. Marieke Kleemans asks why, if moving to a city pays so well, more people do not do it, the same puzzle Pelnik investigates on the scale of a single city's streets. A Microeconomic Perspective on Misallocation. Eric Verhoogen explains why the most productive firms in low-income countries often stay small, a different view of the frictions that stop resources going where they would earn the most. Further readingFrom Street Markets to Shopping Malls: The Modern Service Multiplier, a STEG working paper by Matthew Schwartzman, argues that as supermarkets and restaurants replace street vendors and food hawkers, rising incomes and rising demand for modern services reinforce each other, and estimates that this effect amplified the growth of modern services in Brazil by 25% between 2000 and 2010. How Important are Investment Indivisibilities for Development? Experimental Evidence from Uganda, a STEG working paper by Joseph Kaboski, Molly Lipscomb, Carolyn Pelnik, and Virgiliu Midrigan, offers Ugandans a choice between a safe small cash grant and a risky large one, and finds that 27% take the gamble, a companion piece on how liquidity and risk shape the investment decisions of the poor.

    Moving to profitability

  6. Sep 24

    Why Is There Not More Spousal Insurance?

    Conversations on Transformation, a STEG podcastA wage job in a poor country is a precarious thing. In the poorest economies in Todd Schoellman's sample, more than 20% of wage workers lose their job within three months, against under 5% in rich countries. There is no unemployment cheque, often no savings to fall back on, and in a one-earner household the obvious response is for somebody else to go out and find work. Does that actually happen? Schoellman tells Tim Phillips how he and his co-authors are attempting to answer that question using harmonised labour force survey data that links households from Bolivia to Botswana. Does a wife goes to work when her husband loses his job? The answer is no, in rich countries and poor ones alike. Schoellman presented the paper at STEG's sixth Annual Conference in Nairobi in January 2026, and he talks Tim through a result that surprised him more than almost anything else he has found in 15 years of research. The research behind this episodeBacher, Annika, Kevin Donovan, Philipp Grubener, Lukas Nord, and Todd Schoellman. 2026. "Household Labor Supply Insurance Around the World." Work in progress, presented at the STEG Annual Conference, Nairobi, January 2026, under the working title "Spousal Insurance Around the World." To cite this episodePhillips, Tim, and Todd Schoellman. 2026. "Why Is There Not More Spousal Insurance?" Conversations on Transformation (podcast).About the guestTodd Schoellman is a senior research economist at the Federal Reserve Bank of Minneapolis. He was previously an assistant professor at Arizona State University and Clemson University, and holds a PhD from Stanford University. His research spans labour market dynamics in developing countries, human capital accounting, and the drivers of cross-country income differences. Research cited in this episodeThe Current Population Survey is the source of the US labour market data Schoellman contrasts with the developing world. Running continuously since 1947, it is one of the oldest household surveys that lets researchers track the same worker's employment status from one period to the next, which is exactly what a study of job loss and household response requires. The European Union Labour Force Survey extended this kind of tracking to most of Europe from the 1970s and 1980s onwards. Along with the Current Population Survey, it explains why decades of research into the added worker effect have focused almost entirely on rich countries. Poorer countries simply did not have comparable panel data until recently. The added worker effect is the name economists give to exactly the behaviour Schoellman tests for, a non-working spouse entering the labour force after the main earner loses a job. The term originates with Shelly Lundberg's 1985 paper of the same name in the Journal of Labor Economics, which established the low take-up rates in the United States that this new research now finds hold just as strongly, or just as weakly, across the developing world. Labor Market Dynamics and Development, published by Kevin Donovan, Will Jianyu Lu, and Todd Schoellman in the Quarterly Journal of Economics in 2023, is the earlier project that built the underlying data infrastructure. Schoellman and Donovan spent roughly a decade collecting and harmonising panel labour force surveys from countries that had only recently started building the kind of household tracking data that rich countries take for granted, and that dataset is the foundation for the household insurance question tackled in this episode. More Conversations on Transformation episodesHow much is a formal job worth in Mexico? Brenda Samaniego de la Parra talks to Tim about Mexico's informal economy, the other side of the coping mechanism Schoellman describes, where displaced workers move into self-employment rather than sit idle. How land reforms in China helped women. Ting Chen discusses how the Hukou system and its reform shaped migration and life chances for Chinese women, a different angle on the question of what actually determines whether women enter paid work. Further readingBringing Work Home: Flexible Arrangements as Gateway Jobs for Women in West Bengal, a STEG working paper by Lisa Ho, Suhani Jalota, and Anahita Karandikar, finds that hundreds of millions of women who want paid work stay out of the labour force because the jobs on offer do not fit around their household roles, a possible clue to why Schoellman's wives do not step in even when the household needs the income. Self Employment, Micro-Entrepreneurship, and Development, a STEG synthesis paper by Austin Davis, Eric Hsu, and Mitchell VanVuren, reviews why firms in poorer countries are disproportionately small and self-employment so common, directly relevant to the finding that displaced husbands mostly re-enter work as the self-employed.

    Why Is There Not More Spousal Insurance?

  7. Sep 17

    A Microeconomic Perspective on Misallocation

    Conversations on Transformation, a STEG podcastIn low income countries, the most productive firms often stay small, and the least efficient ones stay in business far longer than they should. Why? Eric Verhoogen presented his answer at January's STEG Annual Conference in Nairobi, drawn from a chapter he is writing for the forthcoming Handbook of Development Economics. He argues that economists have become good at spotting misallocation, but not yet at identifying what causes it and what policy can do to eliminate it. His search for the source takes in tax codes, labour law, credit markets, and a workshop district in Dhaka where firms adopted a more efficient motor. If we find what is causing misallocation, he tells Tim Phillips, the prize could be worth 10 to 30% of GDP. The research behind this episodeBergquist, Lauren Falcao, Danial Lashkari, and Eric Verhoogen. 2026. "Wedges: A Microeconomic Perspective on Misallocation." Forthcoming in Handbook of Development Economics, vol. 6. Also CEPR Discussion Paper 21034 (gated) and NBER Working Paper 34756. Chaurey, Ritam, Gaurav Nayyar, Siddharth Sharma, and Eric Verhoogen. 2025. "Social Learning among Urban Manufacturing Firms: Energy-Efficient Motors in Bangladesh." CEPR Discussion Paper 20713 (gated). To cite this episodePhillips, Tim, and Eric Verhoogen. 2026. "A Microeconomic Perspective on Misallocation." Conversations on Transformation (podcast).About the guestEric Verhoogen is professor of economics and international and public affairs at Columbia University, where he co-directs the Center for Development Economics and Policy. He is a CEPR Fellow in Development Economics. His research spans industrial development in poor countries, covering firm productivity, technology adoption, quality upgrading, and the frictions that keep resources from reaching their best use. Research cited in this episodeWedges is the term economists use for whatever stops resources flowing to their most productive use inside a firm. Verhoogen and his co-authors draw a distinction that is central to their chapter: between distortionary wedges, such as taxes or credit constraints, and technological wedges, such as spillovers, which can produce the same statistical signature even in an efficient economy. Marginal revenue products and TFPR are the standard diagnostic tools of the misallocation literature. If two firms in the same industry get very different returns from an extra worker or an extra unit of capital, something is stopping resources moving from the low-return firm to the high-return one. Chang-Tai Hsieh and Peter J. Klenow, in "Misallocation and Manufacturing TFP in China and India" (Hsieh and Klenow 2009), used this method to estimate that reallocating resources within Chinese and Indian manufacturing to match the dispersion seen in the United States would raise measured productivity by 30 to 50% in China and 40 to 60% in India. It remains the most cited paper in the field. Returns to capital in microenterprises: the "capital drops" that Verhoogen mentions refer to Suresh de Mel, David McKenzie, and Christopher Woodruff's randomised cash and equipment grants to Sri Lankan microenterprises, which found real returns to capital far above market interest rates (de Mel, McKenzie, and Woodruff 2008). It is one of the few settings where researchers have good evidence on how the marginal return to capital varies with firm size, and Verhoogen argues that evidence thins out fast once firms grow beyond the very smallest. Market-access subsidies in Tunisia is a separate Verhoogen experiment, with Nadia Ali, Giacomo De Giorgi, and Aminur Rahman, in which the Tunisian government offered firms grants of $50,000 to help them break into export markets (Ali et al. 2025, CEPR Discussion Paper 20398, gated). It is one of the very few experiments with a large enough cheque to say something about medium sized, rather than micro, firms. India's Industrial Disputes Act historically required firms with 100 or more workers to seek government permission before laying off staff, one of the regulatory wedges Verhoogen discusses. The threshold has since been raised nationally to 300 workers under the Industrial Relations Code, which took effect on 21 November 2025, after this conversation was recorded. PEDL, Private Enterprise Development in Low-Income Countries, is STEG's sister research programme, also coordinated by CEPR, sharing its focus on firms, innovation, and productivity in developing economies. More Conversations on Transformation episodesNo Country for Dying Firms: Evidence from India. Shoumitro Chatterjee talks to Tim about what happens to an economy when failing firms cannot easily go out of business, the flip side of Verhoogen's story about productive firms that cannot easily grow. Navigating Industrial Policy. Beata Javorcik discusses what the return of industrial policy means for economic development, and how governments might avoid repeating the mistakes of the past as they try to correct exactly the kind of distortions discussed in this episode. Further readingMisallocation and Product Choice, a STEG working paper by Stepan Gordeev and Sudhir Singh, finds that ignoring the fact that firms can choose which products to make causes standard models to understate the productivity cost of misallocation between Indian farms by 28%. Financing Costs and Development, a STEG working paper by Tiago Cavalcanti, Joseph Kaboski, Bruno Martins, and Cezar Santos, uses a Brazilian credit registry to show that dispersion in the cost of borrowing, not just credit rationing, drives much of the financial friction that Verhoogen discusses.

    A Microeconomic Perspective on Misallocation

  8. Feb 19

    Structural change in sub-Saharan Africa

    Recorded at the 2025 annual conference of the Structural Transformation and Economic Growth Programme, held at the University of Oxford.We have a mental model of structural transformation, and we have decades of empirical data to test our ideas about how that process works. But does it happen in the same way everywhere? This question has been hard to answer, not least because in some parts of the Global South, data has been easier to locate that in others. New research uses macro and trade data on from Sub-Saharan Africa to analyse whether its development follows those familiar patterns. Tim Phillips spoke to two of the authors: Gaaitzen de Vries of the University of Groningen and Kei-Mu Yi of the University of Houston, and the Dallas Fed.

    Structural change in sub-Saharan Africa
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About

The STEG Podcast Series ' Conversations on Transformation' investigates some of the most important new research in structural transformation, growth and economic development.

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  • Creator
    Structural Transformation and Economic Growth (STEG), led by CEPR
  • Years Active
    2026
  • Episodes
    33
  • Rating
    Clean
  • Copyright
    © CEPR
  • Show Website
    Conversations on Transformation

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