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Electricity theft is a common problem in many countries and
energy worth billions of dollars is stolen annually from electricity
grids. The problem has socioeconomic, political, environmental and
technical roots, but the solution is generally sought solely through
technical measures. This paper empirically investigates the effects of
various factors including electricity price, per capita income,
probability of detection, fines collected from offenders, weighted
temperature index and load shedding, that may explain the theft. The
study employed annual panel data obtained from nine electricity
distribution companies in Pakistan for the period 1988–2010. The study
estimates the Fixed Effects models through the least squares dummy
variable (LSDV) technique and Generalised Method of Moments (GMM). Our
results indicate that per capita income has significant negative and
electricity price a positive effect on electricity theft with
sufficiently high coefficient values. The probability of detection
variable appears with a positive sign in both estimations indicating a
poor deterrence. The results of LSDV show a positive impact of fine on
conviction on electricity theft. But in GMM estimation, this variable
appears with a right sign. The results from both models are robust in
the case of load shedding and temperature variables. The findings show
that economic variables are most significant in explaining electricity
theft. The findings may also be applicable in other developing countries
where hefty amounts of revenues are lost due to electricity theft.
Keywords: Electricity Theft, Fixed Effects Model, Pakistan

The present study develops an integrated assessment model (IAM) for food security under climate change for South Asia. For IAM, initially, an econometric model is estimated that identifies the impact of climate change on crop yields, using the historical relationships between temperature, precipitation, and the production of cereals. Subsequently, future projections have been collected for temperature and precipitation from climate models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5), and the previous econometric model is applied to obtain the implied future cereal yields changes. Then, the yield variations are fed into a multiregional Global Trade Analysis Project (GTAP) model, calibrated to the GTAP 9 database, taking the form of decreases in factor-augmenting productivity of the grains sector. Further, the present study evaluates the effects of climate change on an individual South Asian country. The results indicate that change in climate decreases food production, increases food prices, decreases food consumption, and thus affects the welfare. Trade and fiscal policy responses are investigated to combat the problem of food security. It is revealed that these two policies fail to compensate climate change damage in all the selected South Asian countries.

Greenhouse gas emissions cause climate change, and agriculture is the most vulnerable sector. Farmers do have some capability to adapt to changing weather and climate, but this capability is contingent on many factors, including geographical and socioeconomic conditions. Assessing the actual adaptation potential in the agricultural sector is therefore an empirical issue, to which this paper contributes by presenting a study examining the impacts of climate change on cereal yields in 55 developing and developed countries, using data from 1991 to 2015. The results indicate that cereal yields are affected in all regions by changes in temperature and precipitation, with significant differences in certain macro-regions in the world. In Southern Asia and Central Africa, farmers fail to adapt to climate change. The findings suggest that the world should focus more on enhancing adaptive capacity to moderate potential damage and on coping with the consequences of climate change.

Universal attainment of basic education is recognised as a key
development goal; whereas early-age work is considered as a barrier to
achieving this goal. The literature suggests that returns to education
are larger than those of early-age work, and that child-labour results
in long term social loss that reduces human capital. This study
evaluates the argument that earlyage work can itself lead to
accumulation of human capital when it takes the form of apprenticeship
career path. The paper develops a model that allows a rational agent
(parent) to compare the early-age work as apprenticeship career path
with the formal education career and shows that the parents' career
choice for their child will depend on the lifetime earnings of both
careers. The theoretical model is further extended and empirically
tested to check whether benefits of education are higher for all levels
of education. The simulation analysis suggests that for lower level of
education up to Grade-12, the benefits of apprenticeship exceed the net
benefits of education whereas, at Grade-12 and beyond, the net benefits
of education in terms of earnings outstrip the apprenticeship career.
The study implies that early-age work may not necessarily be inefficient
when compared with low levels of schooling and that any intervention
should ensure universal education for all without compromising skill
development of resource poor children. This can be achieved through
making skill development complementary to education. JEL
Classifications: H44, H52, I26, J24 Keywords: Child-labour, Basic
Education, Human Capital, Public Policy