Portrait of Dr Guy Tchuente

Dr Guy Tchuente

Lecturer in Economics


Dr Guy Tchuente is a Lecturer in Economics who joined the University of Kent in 2014. Prior to his arrival at Kent, he was a Lecturer at the University of Montreal, where he had previously gained his PhD. 

Research interests

Guy’s primary research interests are in the areas of econometrics (theory and applications) and labour economics. He also has an interest in the area of empirical industrial organisation.

He is a member of the Macroeconomics, Growth and History Centre (MaGHiC).



Guy will consider supervising PhD students who are interested in:

  • microeconomics
  • labour economics
  • economics of education.


Guy is a Fellow of the Global Labor Organization and of the UK's National Institute of Economic and Social Research.

Administrative roles

  • European and International Programmes Officer
  • Internationalisation Co-ordinator



  • Tchuente, G. (2016). High school human capital portfolio and college outcomes. Journal of Human Capital [Online] 10:267-302. Available at: http://dx.doi.org/10.1086/687417.
    This paper assesses the relationship between courses taken in high school and college major choice. It considers individuals as holding a portfolio of relative human capital
    rates that may either be similar to those in their major - specialized - or different from those in their major - diversified. Using High School and Beyond survey data, I find
    a U-shaped relationship between the diversification of high school courses portfolio, measured by the differences from the typical student in the major, and college performance.
    The underlying relation linking high school to college is assessed by estimating a structural model of high school human capital acquisition and college major choice.
    Policy experiments suggest that taking an additional quantitative course in high school increases the probability that a college student chooses a science, technology, engineering, or math major by four percentage points with little effect on college performance.
  • Tchuente, G. and Carrasco, M. (2015). Efficient Estimation with Many Weak Instruments Using Regularization Techniques. Econometric Reviews [Online] 35:1609-1637. Available at: http://dx.doi.org/10.1080/07474938.2015.1092806.
    The problem of weak instruments is due to a very small concentration parameter. To boost the concentration parameter, we propose to increase the number of instruments to
    a large number or even up to a continuum. However, in finite samples, the inclusion of an excessive number of moments may be harmful. To address this issue, we use regularization techniques as in Carrasco (2012) and Carrasco and Tchuente (2014). We show that normalized regularized two-stage least squares (2SLS) and limited maximum likelihood (LIML) are consistent and asymptotically normally distributed. Moreover, our estimators are asymptotically more efficient than most competing estimators. Our simulations show that the leading regularized estimators (LF and T of LIML) work very well (are nearly median unbiased) even in the case of relatively weak instruments. An application to the effect of
    institutions on output growth completes the article.
  • Tchuente, G. and Carrasco, M. (2015). Regularized LIML for many instruments. Journal of Econometrics [Online] 186:427-442. Available at: http://dx.doi.org/10.1016/j.jeconom.2015.02.018.
    The use of many moment conditions improves the asymptotic efficiency of the instrumental variables estimators. However, in finite samples, the inclusion of an excessive number of moments increases the bias. To solve this problem, we propose regularized versions of the limited information maximum likelihood (LIML) based on three different regularizations: Tikhonov, Landweber–Fridman, and principal components. Our estimators are consistent and asymptotically normal under heteroskedastic error. Moreover, they reach the semiparametric efficiency bound assuming homoskedastic error. We show that the regularized LIML estimators possess finite moments when the sample size is large enough. The higher order expansion of the mean square error (MSE) shows the dominance of regularized LIML over regularized two-staged least squares estimators. We devise a data driven selection of the regularization parameter based on the approximate MSE. A Monte Carlo study and two empirical applications illustrate the relevance of our estimators.


  • Tchuente, G. (2019). Weak Identification and Estimation of Social Interaction Models. arXiv.org. Available at: https://arxiv.org/abs/1902.06143.
    The identification of the network effect is based on either group size variation, the structure of the network or the relative position in the network. I provide easy-to-verify necessary conditions for the identification of undirected network models based on the number of distinct eigenvalues of the adjacency matrix. Identification of network effects is possible; although in many empirical situations existing identification strategies may require the use of many instruments or instruments that could be strongly correlated with each other. The use of highly correlated instruments or many instruments may lead to weak identification or many instruments bias. This paper proposes regularized versions of the two-stage least squares (2SLS) estimators as a solution to these problems. The proposed estimators are consistent and asymptotically normal. A Monte Carlo study illustrates the properties of the regularized estimators. An empirical application, assessing a local government tax competition model, shows the empirical relevance of using regularization methods.
  • Tchuente, G., Piracha, M. and Tani, M. (2017). Immigration Policy and Remittance Behaviour. IZA. Available at: https://ssrn.com/abstract=3029797.
    This paper analyses the impact of a change in Australia’s immigration policy, introduced
    in the mid-1990s, on migrants’ remittance behaviour. More precisely, we compare the
    remittance behaviour of two cohorts who entered Australia before and after the policy
    change, which consists of stricter entry requirements. Our empirical strategy uses conditional
    difference-in-differences in the presence of interactive fixed-effects. We first show that Bai’s
    (2009) least squares estimator and conditional difference-in-differences are biased if used
    on their own. We then derive conditions that are required to obtain a consistent estimator
    using a combination of conditional difference-in-differences and Bai’s (2009) least squares
    estimator. The results indicate that those who entered under more stringent conditions –
    the second cohort – have a higher probability to remit than those in the first cohort, though
    the policy change has no discernible effect on the level of remittances.
  • Tchuente, G. and Klein, A. (2017). Spatial Differencing for Sample Selection Models. SSRN. Available at: https://ssrn.com/abstract=2875739.
  • Tchuente, G., Some, J. and N. Nganou, J. (2016). Government Spending Multipliers in Resource-Rich Developing Countries. SSRN. Available at: http://dx.doi.org/10.2139/ssrn.2875757.
    This paper estimates government spending multiplier for natural resource-rich lowincome
    countries (LICs). Our estimates suggest an absence of natural resource curse in
    government spending multiplier. In the short-run, the government spending multiplier
    is around 0.7 for natural resource-rich LICs and 0.43 for all LICs. The government
    spending has a permanent impact on the real economic activity in resource-rich countries
    while having a transitory long-run impact in other countries
  • Tchuente, G. and Carrasco, M. (2016). Regularization Based Anderson Rubin Tests for Many Instruments. School of Economics, University of Kent. Available at: https://ideas.repec.org/p/ukc/ukcedp/1608.html.
    This paper studies the asymptotic validity of the regularized Anderson Rubin (AR) tests
    in linear models with large number of instruments. The regularized AR tests use informationreduction
    methods to provide robust inference in instrumental variable (IV) estimation for
    data rich environments. We derive the asymptotic properties of the tests. Their asymptotic
    distribution depend on unknown nuisance parameters. A bootstrap method is used to obtain
    more reliable inference. The regularized tests are robust to many moment conditions in the
    sense that they are valid for both few and many instruments, and even for more instruments
    than the sample size. Our simulations show that the proposed AR tests work well and have
    better performance than competing AR tests when the number of instruments is very large.
    The usefulness of the regularized tests is shown by proposing confidence intervals for the
    Elasticity of Intertemporal Substitution (EIS)


  • Khan, S. (2019). Growth & Labour Market in Developing Countries.
    Economic development is deemed to be the process whereby a low-income nation improves the economic, political and social well-being of its citizen and transform into a modern
    industrialised nation. Although growth is vital and necessary for development, it is not a sufficient condition as development cannot be guaranteed. Over business cycle, growth
    fluctuates and this triggers movement between different labour market states. If there is positive growth, labour market tightness improves and with more vacancies available job finding rate goes up whilst separation rate declines. All in all, more individuals move to employment which in turn improves living standard. Hence, in a way, development, growth and labour markets are all interconnected.

    In this research project, first, we examine the impact of FDI on growth which is considered to be one of the primary determinants. In the literature, there is a debate on-going regarding the effectiveness of FDI on growth due to the conflicting empirical evidences. In addition to that, whilst it is claimed that BRICs over time have attracted quality FDI, there is no empirical support. Therefore, we take this opportunity to derive an augmented Solow model that accounts for different forms of capital investments as well as country-specific institutional characteristics and conduct panel estimations using 32 years of data on 54 developing countries to address those issues. Our main result is that FDI, GDI, human capital and infrastructure are all important factors and promote growth in developing countries. However, only FDI and GDI are more effective in BRICs whilst investment in human capital is detrimental to the growth of BRICs and as such in varying degrees contributed to the growth disparity.

    Second, we elucidate the dynamics of the Brazilian unemployment for the period 2002 to 2014 in the presence of temporary and permanent contracts. In the literature, there has been many studies which address the gross flows, transition rates and unemployment dynamics but almost all focused on developed countries due to the lack of micro-data required for such investigation. The new Monthly Employment Survey (PME-Nova) was modified in 2002 for greater coverage and to make it more aligned for international comparison in line with ILO recommendation. With the availability of information on contracts, we take this opportunity to work out the worker flows and transition rates in a 6-state model and subsequently observe business cycle properties of these transition rates and their contribution to unemployment dynamics so as to compare our findings to those from other countries. Our main result is that transition rates involving permanent contracts are more important in explaining the cyclical fluctuations in unemployment and play a crucial role in job creation but even more so in job destruction.

    Finally, we explore the dualistic nature of labour market in developing countries where there are different tiers of informal job such as informal employer, self-employed and informal salaried. In the literature, informal sector is often claimed to be an unregulated microentrepreneurial enterprise where individuals find work through word-of-mouth
    communication. However, this has never been explicitly modelled. Therefore, we take this opportunity to develop a matching model where the formal sector is characterized by search frictions whilst the informal sector is frictionless and perfectly competitive but comprising of different categories of informal job. Afterwards, this 5-state model is calibrated using the stylized facts from Brazil and a policy simulation is performed. Our main result is that a payrolltax aggravates labour market tightness, deter firms to open new vacancies, reduce search intensity and willingness of workers to leave non-formal states and last but not the least, widens inequality. Therefore, tax plays an integral role in increasing non-employment as wellas the size of informality.
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