SERGIO H. LENCE:
Research Agenda
My past research has mostly focused on the theme
of decision making in the presence of uncertainty. Besides being central to the
theory and practice of finance, the study of decision making under uncertainty
is critically relevant to the U.S.
agricultural sector. This is true because recent policies have given farmers
much more freedom to choose among agricultural enterprises and have shifted
most of the risk-bearing burden back to farmers. As well, nowadays farmers and
agribusiness firms face a much larger degree of uncertainty due to many new factors,
such as greater commodity price volatility, new types of financial
arrangements, stricter food safety standards, and greater public concerns
toward the environment.
Within the unifying theme of decision making
under uncertainty, I published numerous articles and made significant
contributions on the following specific topics:
- Financial markets, the impact of financial markets on real
decisions, and risk management.
- Endogenous risk and self protection. Endogenous risk exists when an
individual can affect the probability that an event will occur. Self
protection occurs when an individual takes actions to change the
probability of him/her suffering a loss.
- Estimation risk (i.e., the uncertainty about parameters of the
probability distribution of random variables such as prices).
- The value of better information about probability distribution
parameters.
- Portfolio models applied to study the allocation of farmland among
agricultural activities.
My research agenda has evolved from being
largely focused on risk management problems towards being concerned with
broader financial issues. My current research agenda includes the study of (1)
asset prices; (2) credit markets; (3) preferences toward time, risk, and intertemporal substitution; (4) investment; (5) land
allocation decisions using portfolio models; and (6) farm behavior using
entropy methods. These research areas are discussed next.
Asset prices. I am
interested in providing a better understanding of the behavior of farmland
prices. Farmland prices are very important because they have experienced
notorious boom-bust cycles with destabilizing effects for the agricultural
economy and related sectors (clear proof of this assertion is the recession
suffered by Iowa
in the 1980s). Farmland accounts for about two thirds of the U.S. farm
sector’s wealth and provides critical collateral for the financing of
agriculture. Specific aspects of farmland price behavior that I am studying
are:
- Rationality. I am investigating whether farmland prices reflect
"rational" expectations of future cash flows from farmland. That
is, I am evaluating how good the models commonly used to appraise farmland
values are.
- Effect of transaction costs. I am assessing the likely impact that
costs involved in the transfer of farmland ownership may have on the level
and volatility of farmland prices.
- Structural changes. I am studying whether the behavior of returns
to farmland investments has changed over time and, if so, the possible
factors behind such structural changes.
- The extent to which prices of farmland with different quality
and/or locations are linked to each other, and the extent to which
farmland markets are related to financial asset markets. I am quantifying
the strength of such linkages, as they provide a measure of how well
farmland markets function.
In addition, I plan to address the price
behavior of other important agricultural assets, such as machinery and
livestock.
Credit markets. I am
exploring the importance of credit rationing in the U.S. agricultural sector.
Governments have historically provided substantial amounts of subsidized credit
to agriculture based on the presumption that credit rationing was pervasive.
Unfortunately, little scientific evidence of credit rationing exists, mostly
because only recently have economists began to
understand rationing behavior. Although I may also use more traditional
economic research methods, I am currently using laboratory experiments to
uncover when credit rationing may occur. Laboratory experiments are quite
useful for this purpose because they allow me to control for the degree of
information possessed by different market participants. This is crucial because
it is now well-known that credit markets differ from other (e.g., commodity)
markets, in that participants typically have asymmetric information (for
example, borrowers may know how likely they are to default better than
lenders). I am also analyzing the
pervasive structural changes experienced in recent years by the agricultural
banking sector.
Preferences toward
time, risk, and intertemporal substitution.
Despite their relevance for understanding investment and saving behavior in the
U.S. agricultural sector, no research has been done to measure the extent to
which U.S. farmers discount the future (i.e., their time preferences) or the
extent to which they substitute current for future consumption when interest
rates change (i.e., their preferences toward intertemporal
substitution). I want to fill this gap in the existing knowledge. As well, part
of my current work is aimed at obtaining empirical estimates of risk aversion
for the U.S.
agricultural sector that are better grounded on financial theory.
Investment. I
have developed a theoretical framework to study investments in equipment by
owner-operated firms (e.g., farms) and how they are affected by credit
constraints. I am currently modeling the U.S.
farm sector, and a student of mine is investigating this topic using panel data
for Iowa
farmers. I am also developing a theoretical model to analyze and measure the
impact on U.S.
farmers’ welfare of transaction costs involved in buying/selling assets.
Portfolio models applied to land
allocation decisions. I am applying
financial portfolio models to study positive and normative issues regarding the
allocation of land among agricultural activities. I am quantifying the extent
to which diversification among agricultural enterprises is due to risk as
opposed to technological constraints.
Application of entropy
methods to study farm behavior. For most farms, data on aggregate input usage are
typically available but data on activity-specific inputs are not. This
limitation of the data makes it difficult to analyze farm behavior (e.g., how
farmers respond to changes in prices or in technology). I am studying farm behavior
using entropy methods, which are newly developed econometric techniques that
allow one to deal with this kind of data limitation in an efficient manner.
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