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BOOK OF ABSTRACTS
6th
International Conference on New Trends
in Econometrics & Finance
2
October 16-18 2020
http://www.icntefconference.com/
3
ICNTEF’2020
6th
International Conference on New Trends in Econometrics &Finance
Published by the ICNTEF Secretariat
Editor:
Assoc. Prof. Dr. Umut UYAR
ICNTEF Secretariat Büyükdere Cad. Ecza sok. Pol Center 4/1 Levent-İstanbul
E-mail: [email protected] http://www.icntefconference.com
ISBN: 978 – 625 – 400 – 506 - 0
Copyright @ 2020 ICNTEF and Authors All Rights Reserved
No part of the material protected by this copyright may be reproduced or utilized in any form or by any means electronic or mechanical, including
photocopying , recording or by any storage or retrieval system, without written permission from the copyrights owners
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SCIENTIFIC COMMITTEE
George Bitros
Athens University of Economics and Business ,Greece
Meryem Duygun
University of Notthingham, UK
Subal Kumbhakar
Binghamton University, USA
Dionisis Philippas
ESCA School of Management, France
Valentin Zelenyuk
The University of Queensland, Australia
5
ORGANIZATION COMMITTEE
Prof. Dr. Mike TSIONAS Lancaster University , UK
Conference Co Chair
Assoc. Prof. Dr. Umut UYAR
Pamukkale University , Turkey
Conference Co Chair
6
Dear Colleagues,
We are proud to announce 6th International Conference on New Trends in Econometrics and
Finance (ICNTEF’20) which will organised fully virtual on dates between October 16 – 18,
2020.
Conference was originally planned for April 2020 but due to the global spread of COVID-19
(Corona Virus) and The Council of Higher Education’s declaration on “Measures to be
Taken in Higher Education Institutions about COVID-19” (March 6, 2020) the conference is
postponed to this current date.
We have published some details on virtual presentations. All informations are available in
conference web site. For more information please do not hesitate to contact
Like the previous conferences, this conference serves is a place for academics, practitioners,
and central bank and government officials in Europe and all over the world to present and
discuss research results about the evolution of the international economics and of the global
financial
In the conference emphasis will be placed on the developments in emerging market
economies, on the fate of the recent trends and of the impact of these developments on
international trade, finance and regulation as well as on national economies and financial
systems. Theoretical, empirical and policy-oriented papers are all welcome.
The organizers encourage submissions of papers and posters on any topic within the overall
theme of the conference and in the areas mentioned in conference topics
Abstract submission deadline is September 30th, 2020 ( Last extension )
All papers will be published in Conference Proceedings Book
We kindly wait for your participation
With my kindest regards
Prof. Dr Mike TSIONAS
Lancaster University, UK
Conference Co Chair
Assoc. Prof. Dr. Umut UYAR
Pamukkale University, Turkey
Conference Co Chair
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16 OCTOBER 2020 FRIDAY
10:40 – 11:00 OPENING CEREMONY
Welcome Speech : Prof. Dr. Mike TSIONAS / Lancaster University – UK
: Assoc. Prof. Dr. Umut UYAR / Pamukkale University - Turkey
Online access : with given username and password
11:00 – 11:30 Keynote Speech:
Professor Serkan ERYILMAZ / Atılım University - Turkey
Statistical Aspects of Wind Energy
11:30 – 11:45 B R E AK
SESSION A
SESSION
CHAIR
Gulder KEMALBAY
TIME PAPER TITLE PRESENTER / CO AUTHOR
11:45 – 12:00 Robust Ranked Set Sampling Methods
for One-Sample T-Test
Yusuf Can SEVIL / Tuğba
YILDIZ
12:00 – 12:15 Polya-Aeppli Process of Order k of
Second Kind with an Application
Meglena LAZAROVA /
Stefanka CHUKOVA & Leda
MINKOVA
12:15 – 12:30 A Statistical Consistent Test Based on
Bivariate Random Thresholds
Aysegul EREM / Ismihan
BAYRAMOGLU
12:30 – 12:45 Performance Analysis of Ridge Deviance
Control
Charts for Monitoring Poisson Profiles
Ulduz MAMMADOVA / M.
Revan OZKALE
12:45 – 13:00 Gompertz-Exponential Distribution:
Record Value Theory and Applications
in Reliability
Shakila BASHIR / Ahmad
Mahmood QURESHI
13:00 – 13:45 LUNCH BREAK
8
SESSION B
SESSION
CHAIR
Fatma NOYAN TEKELI
TIME PAPER TITLE PRESENTER / CO AUTHOR
13:45 – 14:00 On Classification with Multiple Birth
Support Vector Machines
Guvenc ARSLAN
14:00 – 14:15 New Mathematical Formulations for the
Distributed Permutation Flowshop
Scheduling Problem
Alper HAMZADAYI / Hanifi
Okan ISGUDER
14:15 – 14:30 Handling Missing Values in Random
Forests: An Application to Demographic
Survey Data
Duygu ICEN / Ayse
ABBASOGLU OZGOREN &
Anıl BOZ SEMERCI
14:30 – 14:45 Tail Dependence Estimation Based on
Estimation of Kendall Distribution
Function via Rational Bernstein
Polynomials
Mahmut Sami ERDOGAN /
Selim Orhun SUSAM
14:45 – 14:50
( Poster )
POT Method for Ruin Probability in
Infinite Time with Non-Stationary
Arrivals and Heavy Tailed Distribution
Claims or Loss Models
Redhouane FRIHI / Rassoul
ABDELAZIZ
14:50 – 15:00 B R E AK
SESSION C
SESSION
CHAIR
Jale ORAN
TIME PAPER TITLE PRESENTER / CO AUTHOR
15:00 – 15:15 SHARP: A State-Space HAR Model
Using Particle Gibbs Sampling
Aya GHALAYINI / Marwan
IZZELDIN & Mike TSIONAS
15:15 – 15:30 Inflation Targeting, Credibilty and Taylor
Rule: The Estimation of Monetary Policy
Reaction Function for the Central Bank
of Turkey
Gozde YILDIRIM / Ahmet
TIRYAKI
15:30 – 15:45 Machine Learning Extension of the
Simulated Method of Moments for
Estimation of Agent-Based Models
Jiri KUKACKA
15:45 – 16:00 The Impact of Periodicity on Volatility- Sherry LUO / Zhen WEI &
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Volume Relations Marwan IZZELDIN
16:00 – 16:15 B R E AK
16:15 – 16:45 Keynote Speech:
Professor Jale ORAN / Marmara University - Turkey
Behavioral Finance: A Retrospective
17 OCTOBER 2020 SATURDAY
10:30 – 11:00 Keynote Speech:
Professor Rza BASHIROV / Eastern Mediterranean University - North
Cyprus
Statistical Comparison of Modelling Approaches Demonstrated for
Biomedical Networks
11:00 – 11:15 B R E AK
SESSION D
SESSION
CHAIR
Guvenc ARSLAN
TIME PAPER TITLE PRESENTER / CO AUTHOR
11:15 – 11:30 Bell Marginal Models for Longitudinal
Count Outcomes
Hatice Tul Kubra AKDUR
11:30 – 11:45 The Interplay Between Determinism,
Stochasticity And Fuzzyness Illustrated
For P16-Mediated Pathway
Nimet Ilke AKCAY / Rza
BASHIROV
11:45 – 12:00 Modelling Pre-service Mathematics
Teachers Reasoning Under Uncertainty in
the Egyptian Context
Samah Gamal Ahmed
ELBEHARY
12:00 – 12:15 Hypogeometric Distribution and Related
Discrete Time Point Process
Silvana PARALLOJ /
Stefanka CHUKOVA & Leda
MINKOVA
12:15 –13:30 LUNCH BREAK
SESSION E
SESSION
CHAIR
Gulhayat GOLBASI SIMSEK
10
TIME PAPER TITLE PRESENTER / CO AUTHOR
13:30 – 13:45 Different Similarity Measures for the
Clustering of Time Series
Yamina KHEMAL-
BENCHEIKH / Assia
BOUIZANE
13:45 – 14:00 A Method for Constructing and
Interpreting Some Weighted Premium
Principles
Gema PIGUEIRAS / Antonia
CASTAÑO-MARTÍNEZ &
Fernando LÓPEZ-BLAZQUEZ
& Miguel A. SORDO
14:00 – 14:15 A Bayesian Model of COVID19 New
Cases
Marta SANCHEZ-
SANCHEZ / Alfonso
SUÁREZ-LLORENS & Ángel
BERIHUETE
14:15 – 14:20
( POSTER )
A Survey Of Groundwater Quality in
Suburb of Ulaanbaatar City,
Mongoliahydrochemical Investigation of
Groundwater in 14 Th Khoroo of Khan-
Uul District Using Multivariate Statistical
Techniques
Enkhbayar JAMSRANJAV /
Dagvasuren GANBOLD &
Gerelt-Od DASHDONDOG &
Munkhtsetseg ZORIGT
14:20 – 14:30 BREAK
14:30 – 15:00 Keynote Speech:
Professor Agamirza BASHIROV / Eastern Mediterranean University -
North Cyprus
Wide Band Noises: Theory and Applications
SESSION F
SESSION
CHAIR
Aysegul EREM
TIME PAPER TITLE PRESENTER / CO AUTHOR
15:00 – 15:15 Evaluating the Effects of Outliers in
Bootstrap
Ugur BINZAT / Engin
YILDIZTEPE
15:15 – 15:30 An Alternative P Chart For Monitoring
High-Quality Processes Based on
Improved Estimator
Senem SAHAN VAHAPLAR /
Ozlem EGE ORUC
11
15:30 – 15:35
( Poster )
Estimating the Gini Index for Income
Loss
Distributions Under Random Censoring
Bari AMİNA / Abdelaziz
RASSOUL & Ould Rouis
HAMID
15:35 – 16:15 B R E AK
SESSION G
SESSION
CHAIR
Umut UYAR
TIME PAPER TITLE PRESENTER / CO AUTHOR
16:15 – 16:30 Regression Discontinuity Design in the
Analysis of South African Social
Development Praxis
Doug ENGELBRECHT /
Joshua ENGELBRECH
16:30 – 16:45 Assessing The Impact of Microfinance:
Findings From a Survey of Microfinance
Participants in Akole Taluka of
Maharashtra, India
Amita YADWADKAR
16:45 – 17:00 Currency Devaluation Versus Tariff – A
Trade War Simulation
Jen-CHI CHENG / Bryce
ENGELLAND
17:00 – 17:15 Effects of The Epidemic on The Bist
Network Structure
Deniz SUKRUOGLU
17:15 – 17:30 Predictive Power of Exchange Rates and
Interest Rates for Capacity Utilization
and Real Sector Confidence in Turkey
Sıtkı SONMEZER / İsmail
Erkan CELIK
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ABSTRACTS
BEHAVIORAL FINANCE: A RETROSPECTIVE ................................................................................................
Jale Oran ................................................................................................................................................ 14
SHARP: A STATE-SPACE HAR MODEL USING PARTICLE GIBBS SAMPLING ................................................
Aya Ghalayini1, Marwan Izzeldin2, Mike Tsionas3 ................................................................................. 16
INFLATION TARGETING, CREDIBILTY AND TAYLOR RULE: THE ESTIMATION OF MONETARY POLICY
REACTION FUNCTION FOR THE CENTRAL BANK OF TURKEY .....................................................................
Gözde YILDIRIM1, Ahmet TİRYAKİ2 ......................................................................................................... 17
MACHINE LEARNING EXTENSION OF THE SIMULATED METHOD OF MOMENTS FOR ESTIMATION OF
AGENT-BASED MODELS .............................................................................................................................
Jiri Kukacka ............................................................................................................................................ 19
THE IMPACT OF PERIODICITY ON VOLATILITY-VOLUME RELATIONS ........................................................
Sherry LUO1, Zhen WEI2, Marwan IZZELDIN3 ......................................................................................... 22
REGRESSION DISCONTINUITY DESIGN IN THE ANALYSIS OF SOUTH AFRICAN SOCIAL DEVELOPMENT
PRAXIS .......................................................................................................................................................
Doug ENGELBRECHT1, Joshua ENGELBRECHT2. ..................................................................................... 23
ASSESSING THE IMPACT OF MICROFINANCE: ...........................................................................................
Findings from a Survey of Microfinance Participants in Akole Taluka of Maharashtra, India. ................
Amita YADWADKAR1, ............................................................................................................................ 25
CURRENCY DEVALUATION VERSUS TARIFF – A TRADE WAR SIMULATION ...............................................
Jen-Chi Cheng1 and Bryce Engelland2 .................................................................................................... 27
EFFECTS OF THE EPIDEMIC ON THE BIST NETWORK STRUCTURE .............................................................
Deniz ŞÜKRÜOĞLU ................................................................................................................................. 29
PREDICTIVE POWER OF EXCHANGE RATES AND INTEREST RATES FOR CAPACITY UTILIZATION AND
REAL SECTOR CONFIDENCE IN TURKEY .....................................................................................................
Asst. Prof. İsmail Erkan Çelik, Assoc. Prof. Sıtkı Sönmezer.................................................................... 30
13
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BEHAVIORAL FINANCE: A RETROSPECTIVE
Jale Oran Marmara University, Turkey
Undeterred ascent of behavioral finance has been observed since 2000s with the contradictory
evidence in life and markets regarding classical economic theories’ suggestions. Science
inevitably is sceptical about the normative theories’ arguments in any discipline. Rationality
definition of classical economic theories is frequently investigated on such grounds.
As Tversky and Kahneman point out, the deviations of actual behavior from the normative
model are too widespread to be ignored, too systematic to be dismissed as random error and
too fundamental to be accomodated by relaxing the normative model.
Behavioral finance was appreciated for the first time in academic circles with the Nobel prize
in Economics awarded to Prof. Vernon Smith and Prof. Daniel Kahneman together in 2002.
Kahneman’s contribution with prospect theory was quite obvious, while Prof. Smith was
arguing in his 1974 article that “the gap between theories and real life and markets, and need
of new extensions if not new paths, for economic theories to solve the problems in society
and/or market contexts.”
Definition of rationality is somewhat crucial if one is to discuss the individual and
institutional decision making within the context of economics and finance. Fact of life is that,
we are surrounded by a forest of uncertainty and survival depends on how well we perceive
our environment. Therefore, all of the choices we make have some ingredient of uncertainty
and if one talks about decision making, uncertainty must be assumed at the first place. There
are three problems inherent with the rationality. First, people use rules of probability seldom.
Second, they are not aware of context and content. Finally, third problem is about the
incapabilities of brain in making complex calculations.
Human decision making behavior is the concern of many fields, although the way it is
analysed can be quite different. Nevertheless, a priory assumption of self-interest behavior is
not rejected by anyone. People are generally thought to be effective in pursuing their goals,
especially if they have the chance of learning from experience. Optimal decisions increase the
chances of survival in a competitive environment. The appeal of the rational choice axioms
provide an acceptable basis of choice behavior. Simon argues that economics has rather been
preoccupied with the results of rational choice than process of choice, however under the
dynamics of uncertainty in real world, it must advance its understanding using the inputs from
other fields like cognitive psychology, artificial intelligence etc.
According to Mullnathan and Thaler, neo-classical economics defines itself explicitly “anti-
behavioral” by conceptualizing a world populated by calculating, unemotional maximizers,
named Homo Economicus. Some economists defend this view as the model is right, or
standard model is easier to formalize and more relevant. The arguement here is clear: Homo
Economicus is acting rationally to maximize the outcome/benefit. Although one can not argue
against this view, that every creature is after well-being, still the ability of humans
accomplishing this goal is questioned by sceptical researchers and of course by behavioral
economists/finance people that observe the real life phenomena.
15
Thaler calls the people that are less-than-fully-rational as quasi-rational., meaning trying hard
but makes systematic errors. When rational agents interact with quasi-rational agents, one
may expect that rational agents take all the money of quasi-rationals. This is not the case, and
what has been observed is that quasi’s make more money than their rational counterparts,
since they can bear more risk although they don’t prefer to.
In the light of above arguments, behavioral finance has quite strong basis, supported by
research evidence, and is here to stay. As Thaler says, behavioral finance will end, because it
will be a natural ingredient of finance and economics.
16
SHARP: A State-Space HAR model using Particle Gibbs Sampling
Aya Ghalayini1, Marwan Izzeldin
2, Mike Tsionas
3
1Lamcaster University, [email protected] 2Lancaster University, [email protected] 3Lancaster University, [email protected]
Abstract
The purpose of this paper is to present a time-varying HAR model to forecast daily realized
volatility (RV) of the financial markets. Several studies have shown that there are structural
breaks in the RV series and that the parameters are not fixed (Bekierman & Manner, 2018).
We determine that allowing more dynamic specifications in existing extensions of the HAR
model significantly improves the forecasting performance. Hence, we introduce a state-space
HAR model where all the coefficients of the HAR model follow an AR process with
stochastic volatility. Mainly, the variance of the error terms is time-varying where its log
functional form follows an AR process as well. We follow Creal & Tsay (2015) procedure to
estimate the model numerically via the Particle Gibbs Sampling technique by Andrieu et al.
(2010). The proposed general framework can be applied to any AR model while in this paper,
we focus on the HAR model. The forecasting performance is empirically assessed using S&P
500 via the Giacomini & Rossi (2010) fluctuation test to examine the local, as opposed to
global, forecasting performance over the out-of-sample period. We show that the suggested
SHARP model consistently outperforms the HAR and its existing dynamic extensions.
Key Words: Forecasting; HAR; Particle GIBBS Sampling; RV; State-space models
References
[1] Andrieu, C., Doucet, A. & Holenstein, R. (2010), ‘Particle markov chain monte carlo
methods’, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72(3),
269–342.
[2] Bekierman, J. & Manner, H. (2018), ‘Forecasting realized variance measures using time-
varying coefficient models’, International Journal of Forecasting 34(2), 276–287.
[3] Bollerslev, T., Patton, A. J. & Quaedvlieg, R. (2016), ‘Exploiting the errors: A simple
approach for improved volatility forecasting’, Journal of Econometrics 192(1), 1–18.
[4] Creal, D. D. & Tsay, R. S. (2015), ‘High dimensional dynamic stochastic copula models’,
Journal of Econometrics 189(2), 335–345.
[5] Giacomini, R. & Rossi, B. (2010), ‘Forecast comparisons in unstable environments’,
Journal of Applied Econometrics 25(4), 595–620.
[6] Patton, A. J. & Sheppard, K. (2015), ‘Good volatility, bad volatility: Signed jumps and the
persistence of volatility’, Review of Economics and Statistics 97(3), 683–697.
17
INFLATION TARGETING, CREDIBILTY AND TAYLOR RULE: THE
ESTIMATION OF MONETARY POLICY REACTION FUNCTION FOR
THE CENTRAL BANK OF TURKEY
Gözde YILDIRIM1, Ahmet TİRYAKİ
2
1 Ph.D. Student, Department of Economics, Graduate School of Social Sciences, Anadolu University, Eskisehir,
Turkey, E-mail: [email protected]
2 Assoc. Prof. Dr., Open Education Faculty, Anadolu University, Eskisehir, Turkey,
E-mail: [email protected]
Abstract
The Turkish economy, which had suffered from high and chronic inflation problems as in
many emerging economies, started implementing implicit inflation targeting between 2002
and 2005 and adopting an explicit inflation targeting regime since 2006. The inflation
targeting regime adopted by many advanced and emerging economies is a widely accepted
monetary policy strategy for controlling high and variable inflation. However, the success of
monetary policy under the inflation targeting regime depends, to a significant extent, on the
ability to achieve credibility. This study investigates the effects of credibility as well as
inflation gap and real interest rate on central bank reaction function within the framework of
inflation targeting regime in Turkey for the period between 2002:01 and 2019:12 by
employing Autoregressive Distributed Lag (ARDL) and non-linear ARDL (NARDL)
methods.
In this regard, following Tillmann and Neuenkirch (2014), by augmenting the standard Taylor
(1993) rule with an additional term, which is referred as the credibility loss calculated by
Neuenkirch and Tillmann (2014) as the average of past deviations of inflation from the target,
it is being tested whether the central bank takes into account the past deviations from IT in the
current period in order to reestablish credibility, the strength of its response and whether the
central bank responses in a non-linear fashion to such deviations. The credibility loss term
also reflects the nonlinear response of the interest rate to the average past inflation deviations,
as positive past deviations from the inflation target require an additional increase in the policy
instrument in addition to the response to the current inflation gap. Both the ARDL and
NARDL estimation results demonstrate the existence of long-run symmetrical and
asymmetrical cointegration relationship between the policy rate and the real interest rate,
inflation gap and credibility loss.
According to the results obtained from two separate Taylor-type reaction functions as
backward-looking and forward-looking point out that past deviations from the inflation target
feed back into the central bank reaction function and the central bank reacts to positive and
negative credibility loss in a non-linear structure, however, the central bank does not react
compatibly with the theory in order to compensate for the credibility loss. On the other hand,
the backward-looking and forward-looking Taylor rule estimation results reveal that the
central bank mainly considers the inflation gap in accordance with the theory, during the
interest rate adjustment process. The effect of the real interest rate changes on nominal
(target) interest rate is in line with the theory’s expectations. The findings show that since the
development of credibility is strongly associated with expectation management under IT
regime, the central bank needs to put more effective effort on the credibility factor in
expectation management in order to carry out a successful monetary policy strategy.
Keywords: Credibility, Inflation Targeting, Monetary Policy, Taylor rule, NARDL.
18
References
[1] Neuenkirch, M., & Tillmann, P. (2014). Inflation targeting, credibility, and non-linear
Taylor rules. Journal of International Money and Finance, 41, 30-45.
[2] Taylor, J. (1993). Discretion versus Policy Rules in Practice. Carnegie-Rochester
Conference Series on Public Policy, Elsevier, 39(1), 195-214.
19
Machine learning extension of the simulated method of moments for
estimation of agent-based models
Jiri Kukacka
a Institute of Information Theory and Automation, The Czech Academy of Sciences, Pod Vodarenskou vezi 4, 182 00
bFaculty of Social Sciences, Institute of Economic Studies, Charles University, Opletalova 26, 110 00 Prague 1, Czechia
20
21
22
The Impact of Periodicity on Volatility-Volume Relations
Sherry LUO1, Zhen WEI
2, Marwan IZZELDIN
3
1Department Economics, Lancaster University, LA1 4YW, United Kingdom, [email protected]
2Department of Biological Science, Xi’an Jiaotong-Liverpool University, 215123, China, [email protected]
3 Department Economics, Lancaster University, LA1 4YW, United Kingdom, [email protected]
Abstract
Opening, lunch, and closing of financial markets induce a periodic component in the volatility
of high-frequency returns. However, the intraday volume and number of trades also display a
prominent U curve that is still left to be investigated. We propose to use the Seasonal-Trend
Decomposition Procedure Based on Loess to estimate the periodic component in volume and
number of trades. We find that accounting for periodicity improves the explanatory power of
both volume and number of trades on realized variance. Besides, the relationship between the
average absolute return and volume (number of trades as well) can be better modeled using
the mixture of two linear regression models during the trading day. With more analysis on the
posterior probabilities of the mixing components, the average intraday volume and the
number of trades display a higher effect on the absolute return in the morning relative to the
rest of the day. The observed patterns indicate the need to decompose and analyze the
periodicity not only in the realized variance but also in the volume and number of trades.
Key Words: Periodicity, Seasonal-Trend Decomposition Procedure Based on Loess ,
Volatility-Volume Relations, Mixture Models
Reference:
[1] Andersen, T.G., Bollerslev, T., 1997b. Intraday periodicity and volatility persistence in
financial markets. Journal of Empirical Finance 4, 115–158.
[2] Andersen, T.G., Bollerslev, T., Diebold, F.X., Labys, P., 2003. Modeling and forecasting
realized volatility. Econometrica 71, 579–625.
[3] Boudt, K., Croux, C., Laurent, S.., 2011 Robust estimation of intraweek periodicity in
volatility and jump detection. Journal of Empirical Finance 18, 353-367.
23
REGRESSION DISCONTINUITY DESIGN IN THE ANALYSIS OF
SOUTH AFRICAN SOCIAL DEVELOPMENT PRAXIS
Doug ENGELBRECHT1, Joshua ENGELBRECHT2.
1 School of Management, IT and Governance, University of KwaZulu-Natal, South Africa
(corresponding author: [email protected]) 2 School of Built Environment and Development Studies, University of KwaZulu-Natal, South Africa
Abstract
The intense focus on South Africa since democratisation in 1994 has both highlighted grave
social inequalities, and accentuated the exigencies of the state’s economic development plans.
Launched in successive iterations by the ruling party, codification of the National
Development Plan (the most recent iteration) commenced in 2010. The Plan was released in
2011, although implementation stalled until 2013 whereupon national budget allocations
began to reflect the required attention to, and urgency of, development priorities.
Social development is the express objective of a dedicated parliamentary ministry and
national Department of Social Development. Following parliamentary debate and
determination, annual budget allocations are made by central government to the nine
geographic provincial jurisdictions determined in 1994. Each province exhibits a character
related to the unique historical considerations that gave rise to distorted development in this
African country, and each boasts a provincial Department of Social Development.
Annual reporting by these provincial entities is silent on the impact on citizens of investment
in developmental welfare. Reporting instead emphasises the scale and scope of interventions,
undertaken by staff and by contracted civil society organisations. The absence of a suitable
metric of social development outcomes is consequently a notable feature of evidenced
ideologically driven social development praxis.
The research component reported here is element of a broader body of enquiry commenced in
2015 and which remains ongoing. Generally, it seeks to identify with the use of econometric
computation, the impact of social development praxis on social development outcomes.
Specifically, it seeks to establish a measured relationship in respect of categorized
disbursements and the change in multi-dimensional deprivation. Serendipitously, this is
enabled by the escalation in investment and the augmentation of developmental intention,
following the actioning of the National Development Plan in early 2013. Regression
discontinuity design was employed to undertake quasi-experimental modelling of the impact
of social development expenditure, pre- and post-implementation of the National
Development Plan.
The Eastern Cape province was selected for this iteration of the research. Social development
expenditure for the period encompassed by the Eastern Cape Department of Social
Development Annual Reports for the financial years ended March 2010 to March 2018
established the explanatory variable. National Income Dynamics Study panel data available
for the corresponding period, establish the outcome variable.
The objective of this research is to determine a robust statistical measure of an imprecise
concept – human wellbeing. Preceding and similar waves of research have established that
24
social development expenditure is materially associated with changes in manifest social
development. This research wave seeks to more acutely distinguish the scale of the causative
effect. This is enabled by regression discontinuity design, measuring the scale of the change
before and after the escalation in social investment and developmental intention, promoted by
the implementation of the National Development Plan in 2013. Isolating the impact of state
social development investment at the inflexion point the National Development Plan
represents, enables informed reappraisal of how best to action social development praxis.
Key Words: regression discontinuity; social development; measuring development
25
ASSESSING THE IMPACT OF MICROFINANCE:
Findings from a Survey of Microfinance Participants in Akole Taluka of
Maharashtra, India.
Amita YADWADKAR1,
1A-9, Pradnyangad Apartments, Near Sarita Vihar, Opposite P.L. Deshpande Garden, Sinhgad Road, Pune -
411030. Email: [email protected] and [email protected]
Abstract
Microfinance, through Self Help Groups (SHGs), has been a generally successful
developmental intervention in India. It has touched the lives of many poor people, specifically
women, in both rural and urban India. Many studies do try to measure this impact but there
are several problems and obstacles in this. Given this background, we have attempted to try
and assess the impact of microfinance on the rural poor through a primary survey of rural
microfinance participants. The study is focused on identifying and studying the monetary and
non-monetary positive and adverse impacts of the microfinance programme on rural
participants. We have particularly attempted to quantify the monetary impact of the
microfinance intervention on the lives of the participants.
The methodology used is a questionnaire-based survey of 159 microfinance participants of the
Akole taluka of the Ahmednagar district of Maharashtra, India. The data is analysed using
statistical techniques.
The findings show that the main non-monetary benefit of the microfinance programme is that
women find social support and an avenue for enhancing their skills through this. The main
adverse impact we find is that the women have less time to devote to their households due to
their participation in the programme. Regarding the monetary impact the findings show that
the majority of the participants in the sample record a high level of monetary impact of the
programme. Regression exercises show that this impact is greater for the Below Poverty Line
(BPL) participants. It is also seen that factors like the length of membership of SHG, loan
amount and amount of agricultural land owned have negligible impact on the level of positive
monetary impact experienced by the participants. However, the age of participant positively
influences the level of monetary impact experienced. Thus, we conclude that although some
studies show that microfinance does not reach the very poor (Hermes and Lensink, 2007), our
study shows that although the coverage of BPL or poor people in the microfinance
programme is relatively low, the intensity of the benefit they derive from the program is high.
Hence the programme is very relevant for them.
Key Words: Microfinance; Impact Assessment; Self Help Group; Monetary Impact; Non-
Monetary Impact.
26
References
[1] Guha, Samapti;. (2007): Impact of competition on microfinance beneficiaries: evidence
from India. Working Paper (21). Asia Research Centre, London School of Economics and
Political Science, London, UK.
[2] Hermes and Lensink (2007): Impact of Microfinance: A Critical Survey, Economic and
Political Weekly, Vol. 42, No. 6, Feb. 10-16, 2007, pp. 462-465.
[3] Nair, Tara (2005): The Transforming World of Indian Microfinance, Economic and
Political Weekly, Vol. 40, No. 17, Apr. 23-29, 2005, pp. 1695-1698.
[4] Pande, R., Cole, S., Sivasankaran, A., Bastian, G. G. and Durlacher, K. (2012). Does poor
people’s access to formal banking services raise their incomes? London: EPPI-Centre,Social
Science Research Unit, Institute of Education, University of London.
[5] Pattanaik, Debudutta;. (July 2017). Indebtedness and Financial Inclusion: The Alarming
Outcome of Commercial Microfinance in India. Pratibimba – The Journal of IMIS, (Indexed
in Proquest), Vol. 17, Issue 1 (January - June 2017). pp 23-30. ISSN: 0972-5466.
27
Currency Devaluation versus Tariff – A Trade War Simulation
Jen-Chi Cheng1 and Bryce Engelland
2
1. Jen-Chi Cheng, Department of Economics, Wichita State University, Wichita, Kansas, USA 67260-
0078 [email protected]
2. Bryce Engelland, Department of Economics, Wichita State University, Wichita, Kansas, USA 67260-
0078 [email protected]
Abstract
This paper investigates the theoretical viability and consequences of a country depreciating
their currency to counteract a tariff barrier to trade. Utilizing a simulated international
economy with eight fictional nations of varying sizes and construction, it gauges the
effectiveness of currency devaluations against tariff barriers to trade in a commodity market.
The results of the simulation paint a simple but important series of conclusions. First, under
reasonable circumstances devaluation can be used to overcome a tariff barrier to trade.
Second, whereas tariffs can (under certain conditions) increase in effectiveness if countries
band together to implement them in multitude, the effectiveness of currency devaluation
decreases as more countries employ it. Third, when groups of exporting countries employ
devaluation against tariffs, they are at a disadvantage compared to the group of importing
countries. If balance of trade is taken as the only key metric, then a Nash equilibrium can
result wherein both exporters and importers are pulled into a trade war. Fourth, small
countries can successfully employ devaluation to overcome the tariffs of large countries.
Because devaluing countries make most of their gains from the shrinking trade surpluses of
other exporters rather than the growing trade deficits of net importers, small exporters can
counteract the trade restrictions of reasonably larger economies via greater global
competitiveness.
This paper finds that each tactic, be it devaluation or tariff, comes with a cost. If consumer
surplus is taken as a proxy for the standard of living, then a decline in the wellbeing of a
country’s citizens is universal under the successful application of the tactics analyzed in the
simulation. The findings offer important implications for the interminable trade war between
the U.S. and China.
Keywords: Tariffs; Currency Devaluation; Consumer Surplus; Nash Equilibrium; Simulation
28
References
[1] Tan DHY, Chen C (2019) The Chinese Economic Transformation: Views from Young
Economists (edited by LIGANG SONG et al.) 215–236.
[2] McKibbin WJ, Stoeckel A (2017) The Centre for Applied Macroeconomic Analysis
(CAMA) Working Papers No. 53/2017.
[3] Broda C, Limao N, Weinstei DE (2008) The American Economic Review 98(5): 2032–
2065.
[4] Gardner GW, Kimbrough KP (1990) International Economic Review 31(3): 575–588.
[5] Wattleworth M. (1988) International Monetary Fund Staff Papers 35(1): 166–180.
[6] Gilbert J (2009) Utah State University Research Papers in Economics. 2009.
29
EFFECTS OF THE EPIDEMIC ON THE BIST NETWORK
STRUCTURE
Deniz ŞÜKRÜOĞLU
Bulent Ecevit University, Zonguldak,Turkey: [email protected]
Abstract
The rapid spread of the coronavirus (COVID-19) has deeply affected the financial markets in
Turkey as well as all over the world. This study uses network analysis to investigate the
change in the links between the volatilities of BIST 100 (Borsa İstanbul) stocks, in the
aftermath of COVID-19. Analysis has been made using the data of the companies included in
the BIST 100 index from 2007 to the present. We find major changes in the linkages of stocks
and industries, compared to the pre-pandemic period.
Key Words: Network analysis; Sparse VAR; LASSO; Pandemic
30
Predictive Power of Exchange Rates and Interest Rates for Capacity
Utilization and Real Sector Confidence in Turkey
Asst. Prof. İsmJiriail Erkan Çelik Economics Dept. Dogus University) İstanbul, TURKEY
Assoc. Prof. Sıtkı Sönmezer Busines Administration Dept. Beykent University) İstanbul, TURKEY
Abstract—
The level of Capacity Utilization rates may reflect how robust an economy is and may help
researchers to predict other macroeconomic factors. This study focuses on interest rates Euros and
USD dollars for forecasting utilization rates and real sector confidence. Thus, for the period of 2007
and 2019, these two factors are studied to shed light causal relationship with capacity utilization rates.
Similarly, the relation between interest rates and foreign exchange rate with Real sector confidence is
analyzed via regression analysis. Results indicate that interest rates are effective both in capacity
utilization rates and real sector confidence. Lagged returns of USD/TRY are found to be effective in
predicting Real sector confidence but Euro/TRY returns are found to have insignificant effect on both
Capacity Utilization and real sector confidence for the sample period in Turkey.
Keywords— Capacity Utilization rates, Real Sector Confidence, interest rates, foreign
exchange rates
