Ricardo Hausmann

Ricardo Hausmann is the founder and Director of Harvard’s Growth Lab and the Rafik Hariri Professor of the Practice of International Political Economy at Harvard Kennedy School. Under his leadership, the Growth Lab has grown into one of the most well-regarded and influential hubs for research on economic growth and development around the world.

His scholarly contributions have had a significant impact on the study and practice of development. These include the development of the Growth Diagnostics and Economic Complexity methodologies, as well as several widely used economic concepts, such as Dark Matter, Original Sin, and Self-discovery. His work has been published in some of the top journals in the world, including Science, Journal of Development Economics, Journal of International Economics, Proceedings of the National Academy of Sciences, Journal of International Money and Finance, Economic Policy, and the Journal of Economic Growth, among many others. These publications have been cited more than 59,000 times.

Since launching the Growth Lab in 2006, Hausmann has served as principal investigator for more than 50 research initiatives in more than 30 countries, including the US, informing development policy, growth strategies, and diversification agendas at the national, regional, and city levels.

Before joining Harvard University, he served as the first Chief Economist of the Inter-American Development Bank (1994-2000), where he created the Research Department. He has served as Minister of Planning of Venezuela (1992-1993) and as a member of the Board of the Central Bank of Venezuela. He also served as Chair of the IMF-World Bank Development Committee. He was Professor of Economics at the Instituto de Estudios Superiores de Administracion (IESA) (1985-1991) in Caracas, where he founded the Center for Public Policy. He holds a Ph.D. in economics from Cornell University.

Download CV (last updated February 2026)

Jordan: The Elements of a Growth Strategy

In the decade 1999-2009, Jordan experienced an impressive growth acceleration, tripling its exports and increasing income per capita by 38%. Since then, a number of external shocks that include the Global Financial Crisis (2008-2009), the Arab Spring (2011), the Syrian Civil War (2011), and the emergence of the Islamic State (2014) have affected Jordan in significant ways and thrown its economy out of balance. Jordan’s debt-to-GDP ratio has ballooned from 55% (2009) to 94% (2018). The economy has continued to grow amidst massive fiscal adjustment and balance of payments constraints, but the large increase in population – by 50% between 2008 and 2017 – driven by massive waves of refugees has resulted in a 12% cumulative loss in income per capita (2010-2017). Moving forward, debt sustainability will require not only continued fiscal consolidation but also faster growth and international support to keep interest payments on the debt contained. We have developed an innovative framework to align Jordan’s growth strategy with its changing factor endowments. The framework incorporates service industries into an Economic Complexity analysis, utilizing the Dun and Bradstreet database, together with an evaluation of the evolution of Jordan’s comparative advantages over time. Combining several tools to identify critical constraints faced by sectors with the greatest potential, we have produced a roadmap with key elements of a strategy for Jordan to return to faster, more sustainable and more inclusive growth that is consistent with its emerging comparative advantages.

What Should We Do About Inequality?

Inequality is the result of many different phenomena. Some of them should be a source of policy concern while others should not. My main problem is the inequality that arises from differences in productivity—namely, differences in productivity across regions, across cities, within cities and across social groups. We know that there are huge differences in income across countries of the world: the richest countries are 200 to 300 times richer than the poorest countries in per capita terms. That’s inequality at the global scale.

That is mostly caused by differences in productivity. It’s not because there’s a global pie and it is shared unequally between the rich countries and the poor countries. These are just independent pies of radically different size. At the global level, the bulk of inequality across countries is inequality in productivity.

Our research has uncovered that in the developing world, there are enormous differences in productivity within countries, across their different regions. For example, in the US, the richest state, which is probably Connecticut, is about twice as rich as the poorest state, which is either Mississippi or West Virginia. The difference is a factor of two. In Mexico, the difference between Chiapas and Nuevo León is a factor of nine. Similar differences exist between the Indian states of Bihar and Goa or between the cities of Patna and Bangalore. These differences in income are mainly differences in productivity. It’s not the result of what share of the pie goes to capital and what size of the pie goes to labor. It is differences in the sizes of the pie.

So there are these enormous differences in productivity that make the productive places rich and the unproductive places poor. The poor people are not being exploited. They’re being excluded from the higher productivity activities. It’s not that the capitalists are taking a very large share of what they produce. It’s just that they produce very little in the first place.

Many of those that worry about inequality blame capitalism for it. Even Pope Francis has been framing the issue in this way. Now, let’s define capitalism the way Karl Marx did. It is a mode of production where some people own the means of production and others work as wage laborers for them. But if this is the case, capitalism hires 8 out of each 9 workers in the USA, 2 out of 3 in Nuevo Leon, 1 out of 7 in Chiapas and 1 out of 19 in India. Places where more of the labor force works for capitalist firms are richer, because capitalist firms allow for much higher productivity.

Poor places are characterized by the absence of capitalist firms and by self-employment, employment: these are small peasants and farmers or owners of small shop. In these settings, there are no wages, there’s no employment relationship. There are no pensions. There is no unemployment insurance. The trappings of a capitalist labor market do not exist.

While Marx thought that capitalism, as a form of organizing production, would take over the world, poor countries and regions are characterized by the absence of capitalism, of capitalist forms of production.

So the question we should ask ourselves is why did capitalism not succeed in these regions, leaving huge differences in productivity between the places where it succeeded and the places where it did not? The answer we have found is that modern capitalist production requires the simultaneous access to many different inputs.

For example, let’s look at Harvard Kennedy School: to operate, it needs electricity and access to the Internet. It needs an urban transportation system for its diverse staff to be able to go to work. It needs the ability to hire a faculty with very different talents, so as to produce what we produce. The lack of any one of these inputs has disastrous consequences. The day the lights go out, the school cannot operate. The day the Internet goes out, our productivity suffers: students will not know what to read for what courses, which events to attend, and we wouldn’t be able to do any research.

So access to all these inputs is necessary for productivity to happen. Absence of any one of these inputs has devastating effects. So this characteristic of modern production means that for places to be productive, they have to have everything.

The conditions for high productivity are very hard to achieve everywhere, but much easier to achieve in a few places. So governments are faced with the dilemma between concentrating all the inputs in a few places, and then getting the benefits of that concentration but also the inequality between those areas and the rest of the country, or trying to be very democratic in assigning inputs—say, electricity in a few places and roads in other places and internet access in some other places. Then no place has everything and if no place has everything, modern production becomes impossible everywhere.

I think that the deep underlying reason for this dilemma is the presence of increasing returns to the inputs. What do we mean by that? Simply that the cost structure of the input involves some fixed cost and then some variable costs. Consider each time we connect a house to the water network, the electricity network, the urban transport network, the road network, the educational system network, the labor market, or the banking system. All of these require someone to pay a fixed cost of connection. The fixed cost may be the copper wire or the pipes or the road that hooks up your home to these networks, the bus line that goes by your home, the accessibility to a labor market that you can go to work in and get back home in the evenings. These fixed costs are independent of whether a household is going to consume 100 kilowatts, 1000 kilowatts, or 5000 kilowatts [of electricity], or whether it’s going to consume 10 liters of water, 50 liters of water, or 1000 liters of water.

Then there’s a variable cost. That depends on how many kilowatts you consumed or how much water you consumed. But first you have to put in the wire or you have to put in the pipes or you have to build the road.

These fixed costs create increasing returns because the more you consume, the cheaper is the total cost per unit. Paying for these fixed costs becomes a headache because if somebody is expected to be poor, you don’t want to open a bank account for him because the fixed cost of opening a bank account is not going to be recouped through the little money or the few transactions that a poor person is going to make. So banks decide not to include the poor. The same thing happens with other services: if you are going to consume very few kilowatts or kilobytes, it doesn’t pay to connect you and if your expected wage is low relative to a bus ride, it does not pay to commute to work. As a consequence, this generates a trap in which you don’t connect people because they’re poor and because they’re not connected, they’re unproductive and hence poor.

This is a fundamental dilemma that needs to be addressed if we are to tackle the inequality problem and I think it is an issue that hasn’t been sufficiently emphasized.

There are two classes of solutions to this problem. The first one is that some technological innovations might reduce those fixed costs and if the fixed cost is reduced, more people can be included. For example, in India today, cell phone penetration is upwards of 80 percent. Landline penetration is, on the contrary, two percent. Why would this be the case? It’s not because landlines are a more recent technology that has not had the time to diffuse. It is because the fixed cost of connecting a home to the landline network is much higher than the fixed cost of buying a cell phone. As a consequence, cell phone technology diffused at light speed while landlines have not diffused. In fact, cell phones have a larger penetration than piped water, which covers less than 50 percent of the population. So technologies diffuse when the fixed costs are low and if technologies can be invented to lower these fixed costs, it facilitates diffusion.

Lowering the fixed cost was also the idea behind micro lending. Traditional banks don’t give small loans because the fixed cost of processing them is too high and would require unaffordable interest rates. So they exclude the customers that would have required a small loan, mainly the poor. Innovations in micro lending are all about reducing that fixed cost of lending, through ideas such as group lending. Mobile banking might allow us to further reduce these fixed costs.

The alternative to a technological solution is to have a policy that shares the fixed cost. A good example comes from the U.S. The Continental Congress in 1775, a year before the Declaration of Independence, decided to create a U.S. post office. They decided to put a post office in every incorporated city in the US. The postal system was the Internet of its time. They decided to pay collectively for that system and to have a flat rate so that any place within the country could communicate with any other place within the country. That is an example of sharing the fixed cost. Had it not been designed that way, small or poor towns would have been excluded and everybody else would have lost the opportunity to communicate with them. We can paraphrase the policy as saying: “We want a network where everybody is connected and we will use policy to make sure it happens.”

So policies can be very important in determining the universality of access to some inputs. I think it’s very important to have a serious discussion of what are these inputs that need to be accessed universally and what is a reasonable strategy to get there.

Career Dynamics and Gender Gaps among Employees in the Microfinance Sector

Microfinance institutions (MFIs) are commonly identified as empowering women and making them key actors in generating social change and economic development. Yet little is known about the gender parity among employees within the lending institutions themselves and how this can impact development. While MFIs are increasingly important as employers in the developing world, there is little micro-level evidence about gender differences among MFI employees and MFIs’ relation to economic development. We use a unique panel dataset of employees from Latin America’s largest MFI to show that gender gaps favouring men for promotion exist primarily in the sales division, while there is a significant gender wage gap in the administrative division. Among loan officers in the sales division, the gender gap in promotion and wages reverses. Finally, female employees tend to work with clients with better loan terms and a history of loans with the institution.

Place-specific Determinants of Income Gaps: New Sub-National Evidence from Chiapas, Mexico

The literature on income gaps between Chiapas and the rest of Mexico revolves around individual factors, such as education and ethnicity. Yet, twenty years after the Zapatista rebellion, the schooling gap between Chiapas and the other Mexican entities has shrunk while the income gap has widened, and we find no evidence indicating that Chiapas indigenes are worse-off than their likes elsewhere in Mexico. We explore a different hypothesis. Based on census data, we calculate the economic complexity index, a measure of the knowledge agglomeration embedded in the economic activities at a municipal level in Mexico. Economic complexity explains a larger fraction of the income gap than any individual factor. Our results suggest that chiapanecos are not the problem, the problem is Chiapas. These results hold when we extend our analysis to Mexico’s thirty-one federal entities, suggesting that place-specific determinants that have been overlooked in both the literature and policy, have a key role in the determination of income gaps.

Measuring Venezuelan Emigration with Twitter

Venezuela has seen an unprecedented exodus of people in recent months. In response to a dramatic economic downturn in which inflation is soaring, oil production tanking, and a humanitarian catastrophe unfolding, many Venezuelans are seeking refuge in neighboring countries. However, the lack of official numbers on emigration from the Venezuelan government, and receiving countries largely refusing to acknowledge a refugee status for affected people, it has been difficult to quantify the magnitude of this crisis. In this note we document how we use data from the social media service Twitter to measure the emigration of people from Venezuela. Using a simple statistical model that allows us to correct for a sampling bias in the data, we estimate that up to 2,9 million Venezuelans have left the country in the past year.

Increasing Your Chances of Success while Leaving Your Comfort Zone: Adapting Sri Lanka’s Growth Model

View Ricardo Hausmann’s presentation to the Ministry of Development Strategies and International Trade.

Appraising the Economic Potential of Panama: Policy Recommendations for Sustainable and Inclusive Growth

This report aims to summarize the main findings of the project as gathered by the three baseline documents, and frame them within a coherent set of policy recommendations that can help Panama to maintain their growth momentum in time and make it more inclusive. Three elements stand out as cornerstones of our proposal:

(i) attracting and retaining qualified human capital;

(ii) maximizing the diffusion of know-how and knowledge spillovers, and

(iii) leveraging on public-private dialog to tackle coordination problems that are hindering economic activity outside the Panama-Colón axis.

Career dynamics and gender gaps among employees in the microfinance sector

While microfinance institutions (MFIs) are increasingly important as employers in the developing world, there is little micro-level evidence on gender differences among MFI employees and MFIs’ relation to economic development.

We use a unique panel dataset of employees from Latin America’s largest MFI to show that gender gaps favouring men for promotion exist primarily in the sales division, while there is a significant gender wage gap in the administrative division. Among loan officers in the sales division, the gender gap in promotion and wages reverses.

Finally, female employees tend to work with clients with better loan terms and a history of loans with the institution.

Institutions vs. Social Interactions in Driving Economic Convergence: Evidence from Colombia

Are regions poor because they have bad institutions or are they poor because they are disconnected from the social channels through which technology diffuses? This paper tests institutional and technological theories of economic convergence by looking at income convergence across Colombian municipalities. We use formal employment and wage data to estimate growth of income per capita at the municipal level. In Colombia, municipalities are organized into 32 departamentos or states. We use cellphone metadata to cluster municipalities into 32 communication clusters, defined as a set of municipalities that are densely connected through phone calls. We show that these two forms of grouping municipalities are very different. We study the effect on municipal income growth of the characteristics of both the state and the communication cluster to which the municipality belongs. We find that belonging to a richer communication cluster accelerates convergence, while belonging to a richer state does not. This result is robust to controlling for state fixed effects when studying the impact of communication clusters and vice versa. The results point to the importance of social interactions rather than formal institutions in the growth process.