Teng joined the Hull University Business School from Hertford
College, University of Oxford, where he held the position of
Lectureship in Economics from 2011-2013 after his Ph.D. from
University of Essex. Teng Ge took the MSc in Public Policy
Economics at University of Hull (2004) and then went on to study
for his second MSc (2005) at Essex, where he also finished his Ph.D
Teng’s research is primarily concerned with applied and
theoretical microeconomics, with particular interests in the labour
market. Current research focuses on how the specific mechanics of
the job matching process affect employment flows and wage
determination. Other research topics include house price dynamics,
human capital skill portfolios and income distribution. Teaching
interests include not only labour but also macroeconomics,
industrial economics and public economics. Recent paper on China’s
Migration puzzle have won the “Best Ph.D Paper” granted by China
Economic Association (UK/EU). Teng is a member of SOLE/EALE, and
PhD (Essex), MSc (Essex, Hull), BSc (Beijing Jiaotong),
PCAP (Hull), FHEA (UK).
Teng’s teaching fields include Microcosmic/Macroeconomic Theory
and Mathematical Analysis.
Applied Microeconomics, Labour Economics, Public Economics,
“Urbanization, Inequality and Property Prices: Equilibrium
Pricing and Transaction in the Chinese Housing Market”, (with Tao
China Economic Review, July, 2016.
"Does Search Boost Efficiency?", Economic Letters, 2015 May, Vol
“Cyclical Behaviours of Labour Market Flows: a
Search-and-Matching Approach”, in Zhongmin Wu
(eds): China in theWorld Economy, ISBN: 9780415470025, chapter
8, pp156-180, Routledge, Taylor&Francis Group, 2009.
“Search, Migration, and Social Connections: The Puzzle of
Migration to Beijing”
“The Optimal Redistributive Taxation in a Model of Assortative
“Inequality, Sorting, and Property Market”,
with Ali Moghaddasi Kelishomi (Warwick) and Tao Wu (JXUFE).
“Reforming the Pension: Growth, Fertility and Population Aging,”
(with David Ong, Peking University)
“Search in the Friendship Social Network”.