As part of our interview series, we ask renowned experts in the field about the future of research in development economics, and for their advice to young researchers. For this interview, we got the opportunity to talk to Prof. Kristina Manysheva.
Kristina Manysheva is an Assistant Professor within the Economic Division at Columbia Business School. Her research focuses on the macroeconomic aspects of economic development. She uses macro models that incorporate empirically motivated micro-economic features, such as heterogeneity and market frictions, to evaluate the quantitative impact of various policies and institutions in a general equilibrium setting.
ETRM: Our first question, what inspired you to do research and development economics from a macro perspective?
Manysheva: That’s a good question. I think it goes back both to my personal story and to what excites me in terms of research, and where I think there are gaps in our understanding of developing countries. I’ve always been drawn to macroeconomics—prior to my PhD, I worked in the macroeconomic department of my home country’s government. So macro was always going to be part of the equation. But equally important is where I’m from. Coming from a developing country, it felt unnatural to focus my research on advanced economies like the U.S. or Europe. I wanted to understand the structural challenges that countries like mine face.
During my second year in graduate school, I discovered what was then a relatively niche but growing field: macro development. I had a moment of clarity—this was exactly the intersection I cared about. It allowed me to combine a deep interest in macroeconomic frameworks with an opportunity to studying development in low-income settings.
As I explored the literature, I realized how underrepresented developing countries are in macro research. The overwhelming majority of macro studies focus on advanced economies. Yet macroeconomic issues—fiscal policy, structural transformation, productivity—are just as, if not more, critical in lower-income countries.
There’s also a broader motivation behind this work. Ultimately, we do research to help improve living standards. Microeconomic studies have made enormous contributions in that direction, particularly by identifying mechanisms and local effects. But when it comes to large-scale policy interventions—think of structural reforms or major redistribution policies—general equilibrium considerations become essential. Price adjustments, spillovers, labor reallocation—these are core to understanding overall impacts.
Another key aspect is distributional impacts and welfare. Governments don’t just care about average or aggregate income—they care about how the poorest are affected. So, these questions are crucial, and we still don’t fully have the tools or data to answer them. Some of it is due to gaps in the macro development toolkit, some due to data availability, but another tough issue is the training of economists in this area given that it is still a very young field.
ETRM: What do you see as the most exciting or promising frontiers in your field of research now?
Manysheva: I think macro development remains a relatively young but rapidly evolving field. Much of its recent progress has come from combining rigorous microeconomic evidence with macroeconomic frameworks, particularly as computational tools have improved. And in development, heterogeneity is not a detail — it’s central. Differences across firms, households, and regions sometimes make modeling and empirical work more complex than in advanced economies.
A good example is microfinance. The original hope was that relaxing credit constraints would catalyze firm growth and broader development. And while access to finance does improve certain outcomes, we don’t observe the emergence of large, transformative firms in response. That doesn’t mean finance is irrelevant—if you ask firms, access to capital consistently comes up as among primary constraints in any survey. But the evidence shows that in this case removing a single friction isn’t enough.
This leads to what I see as one of very promising directions in the field: understanding the interaction of multiple frictions. In low-income settings, there’s rarely a single constraint holding firms or households back. A firm might gain access to credit but still face weak demand, which itself may be limited by poor infrastructure, fragmented markets, or lack of consumer connectivity. Addressing one bottleneck in isolation often doesn’t deliver meaningful change unless complementary frictions are also tackled.
Another exciting aspect is the increasing use of richer empirical evidence to inform macro modeling. For example, an RCT might show a productivity increase and higher profits, yet firms don’t adjust their inputs. From a macro perspective, that’s puzzling. Why aren’t firms adjusting? Are there labor or capital market frictions? Have we mis-specified the production technology? These insights push us to refine our models and to think more carefully about the mechanisms driving behavior.
Ultimately, the frontier lies in identifying which frictions matter, in which contexts, and how they interact. The answers are unlikely to be one-size-fits-all, and that’s precisely what makes macro development so intellectually rich.
ETRM: How do you typically identify research questions, and what guides your decision to pursue certain ones over others?
Manysheva: I generally rely on two main sources of inspiration for research questions: data exploration and travel.
First, data. Take the project I presented at today’s Cornell Development Seminar about “Land Property Rights, Financial Frictions, and Resource Allocation in Developing Countries” . It began when I came across a panel dataset from Malawi. I started by running some exploratory analyses just trying to get a sense of the patterns. One thing stood out: occupational choice was strongly correlated with land ownership. That immediately raised questions. If people choose occupations based on comparative advantage, why should land ownership matter so much?
I casually brought this up to a friend from Uganda over lunch. He immediately said, “Well, land property rights here aren’t well defined.” That conversation triggered a deeper reflection on how land tenure insecurity limits collateral, restricts occupational mobility, and distorts broader resource allocation. The project grew from there.
The second major source of ideas comes from traveling and engaging directly with the environments I study. I strongly believe that it’s essential for development economist to spend time in the countries they study — to talk to people, observe local institutions, and ask questions. I ask a lot of informal questions to people I casually meet in parks, on buses, in markets. What limits your choices? What influences that decision. People are often surprisingly eager to share their experience. Often, the most valuable insights come not from formal surveys, but from these conversations that reveal how economic and institutional constraints play out on the ground.
Finally, I try not to dive into the literature too early. Instead, I usually sketch a explore a data before reading everything. That way, I preserve independent thinking and don’t anchor my ideas too quickly. Yes, there’s a risk someone else has asked the same question – but even then, I find that starting from a place of curiosity often leads me somewhere new.
ETRM: Your research touches on highly active areas-like innovation, frictions in land and credit markets, and factors explaining persistence of inequality. What do you see as the unique contribution of a macroeconomic approach to understanding these issues?
Manysheva: Macroeconomics contributes in several ways. First, it allows us to think in general equilibrium terms. That’s essential when studying large-scale effects—particularly those that affect distribution and aggregate welfare. Policies rarely operate in isolation; their effects ripple through markets, influencing prices, wages, and resource allocation. General equilibrium models provide a framework for tracing those effects.
Second, macro offers a theoretical lens that can help refine micro-level interventions. Even if we’re not running field experiments ourselves, macroeconomists ask often different questions: What happens to factor reallocation? Are there spillovers? How do prices respond? This perspective can shape not only how we interpret empirical results, but also how interventions are designed.
This is why collaboration between macro and micro researchers is so valuable, especially at the stage of designing empirical work. Take a productivity intervention. A macroeconomist would naturally ask whether the firm subsequently adjusted its inputs—did it hire more workers? Invest in capital? If not, that prompts further questions: Are there frictions in the labor or capital markets? Are we misrepresenting the firm’s production technology? These are questions rooted in macro models.
Macroeconomics also brings tools that are particularly useful for thinking about large-scale reforms—those we can’t experiment on. Models allow us to simulate counterfactuals that would be infeasible or unethical to test in the real world. In that sense, macro offers a kind of “laboratory” for studying the economy at scale. Of course, models are simplifications—but they’re also flexible and relatively inexpensive compared to running large field experiments.
Microeconomics is deeply theoretical as well, but typically focused on the behavior of individuals or firms. Macroeconomics complements that by connecting individual behavior to aggregate outcomes. When studying inequality, structural transformation, or institutional frictions, that connection becomes essential.
ETRM: Given that your work addresses pressing issues in developing countries, do you approach your research with policy impact in mind? If so, how do you engage with the right stakeholders or communicate your findings beyond academia?
Manysheva: Absolutely. I think most of us who work in development are motivated by the potential for real-world impact. But there’s a gap between academic research—especially at the frontier, where work can be highly technical—and the needs of policymakers. As a community, we need to do more to bridge that.
Personally, I often engage through international organizations like the IMF or the World Bank. These institutions are well-positioned to act as intermediaries. For instance, I work on a paper relevant to South Africa, so I have reached out to someone at the IMF South Africa country team to see how my work might be relevant for the policies. That kind of engagement can be surprisingly effective.
Direct collaboration with local governments in developing countries is harder. I’ve worked in one, and I know firsthand how many institutional and bureaucratic barriers exist. There’s real interest in evidence-based policy, but often limited capacity or bandwidth to absorb and implement new research. That’s why partnerships with multilaterals, donors, or NGOs—who often have deeper, more sustained relationships on the ground—are often the most effective way to ensure that our work is seen and used.
ETRM: How do you see innovation shaping economic growth in developing countries, especially with today’s global challenges?
Manysheva: That’s a big question. I think we need to distinguish between innovation as production and innovation as adoption.
In most low-income countries, it’s unlikely that we’ll see large-scale production of frontier innovation in the near term. Innovation is resource-intensive—it requires robust financial systems, high human capital, and supportive institutional environments. Many developing countries simply are not in that position.
That said, adoption of innovation can still be transformative. The challenge is that most innovations are designed for advanced economies, where profit opportunities are clearer. For firms in the global North, developing countries often don’t represent an attractive market—returns are uncertain, infrastructure is lacking, and preferences or constraints may differ substantially.
This is why certain types of innovations—such as the malaria vaccine—struggle to attract private investment. There just isn’t a profitable market in the traditional sense. In that case, donor agencies and global health organizations had to step in to fill the gap. The same logic applies to many other technologies, like capital equipment or climate-resilient agricultural inputs, where adaptation to local conditions is essential.
Sometimes, technologies can transfer easily—a textile machine developed in the U.S. might also work well in Ghana. But in sectors like agriculture, where climate, soil, and institutional structures vary dramatically, off-the-shelf solutions might not be effective.
To address this, we need both targeted government policies and sustained donor involvement to support innovation ecosystems and ensure technologies are designed or adapted with local needs in mind. Without that intentional investment, the global innovation frontier is unlikely to translate into inclusive growth for the world’s poorest regions.
ETRM: Thank you so much for joining our interview today!
