Fiscal Policy And Trade Openness On Unemployment Essay

Fiscal Policy And Trade Openness On Unemployment Essay
AHMED SALIM NUHU On The Impact of Fiscal Policy and Trade Openness on Unemployment in
Namibia 1. Introduction Unemployment remains a fundamental challenge for policy makers around
the globe as it simultaneously increases poverty and threatens social stability within a country
(Goker, 2013). Even though the literature recognizes the critical role fiscal policy plays in mitigating
unemployment and stabilizing the economy (Auerbach, Gale, and Harris, 2010), the extent to which
it works effectively to achieve this remains an issue of debate amongst economists (Coate and
Battaglini, 2011). However, the massive use of fiscal policy tools by governments in the wake of the
2008 financial crisis has, ignited a renewed interest in examining the role of fiscal policy in
promoting growth and employment (Feldstein, 2009). A cursory survey at the literature however,
reveals a lack of consensus on the fiscal policy–unemployment debate. For example, using a
dynamic stochastic general equilibrium model with search and matching frictions, Gomes (2010)
found mixed responses of unemployment to different fiscal shocks. Bruckner and Pappa (2012)
found that an increase in government consumption expenditure usually causes higher unemployment
whilst Fatas and Mihov (2001) in their study of the United States economy and more recently, Unal,
(2015) in his study of the Netherlands economy and, found that higher government consumption
was an incentive for increases in employment. These heterogeneous
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Model of Russian Economy: Research Paper
The paper develops a model of a Russian economy. The model has various equations that cover
government revenues, government expenditure, labour market, interest rates, and variables of
national accounts. The model analyses the impact of changes in the variables of economic policy
and the prices of oil. The model is characterized with comprehensive statistical features and history
in the estimation period running to 2008. From the simulation of the model, it is clear that the
economy of Russian is vulnerable to fluctuations in the price of oil. Consequently, there is an
evidence of economic growth when the oil price growth is absent. From the beginning, the paper
describes the oil market and significance to the economy of Russia. Thereafter, the model is
introduced, followed by a discussion of the equations, estimation guidelines, empirical results,
analysis of the model performance, and model modifications (Robinson, 2013).
Oil Economy of Russia`
The economy of Russia was forecast to grow in 2013 at a lesser pace anticipated at the beginning of
the year and its performance will be better in 2014. This is attributed to weak tapering consumer
demand and weak investment. In 2014, the Gross Domestic Product rose by 1.4% contrary to the
expectations of 3.2%. The economists are pessimistic about the wellbeing of their economy come
2015, forecasting a growth of 2% against the 2.5% for the ministry's economy. The vast economic
parameter of Russia is controlled by oil production.

Foreign Aid and Economic Growth in the Developing...
ABSTRACT OF THE THESIS Using cross–country data, I examine how foreign aid affects
economic growth in developing countries over the period from 1975 to 2000. I find evidence that
foreign aid significantly and negatively correlates with growth in developing countries. However,
foreign aid to inland countries as well as to South Asian countries during the period of 1992–2000 is
found to have a positive impact on growth. In addition, a strong divergence trend is found among
countries in the data set. The results suggest that (i) there may be problems in the present aid
providing system, where aid hinders growth of developing countries (ii) the successful experience of
some inland countries and South Asian nations during the period of ... Show more content on
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1.3. Organization of the Study The study is organized as follows. Chapter II reviews the literature
with various outcomes shown by different authors with different views and models. Chapter III
provides an overview of the regions in the study. Chapter IV describes the data and methodology.
Empirical results and policy implications are discussed in chapter V. Chapter VI concludes the study.
Chapter II Literature Review In general, aid is found to have a positive impact on economic growth
through several mechanisms (i) aid increases investment (ii) aid increases the capacity to import
capital goods or technology (iii) aid does not have an adverse impact on investment and savings (iv)
aid increases the capital productivity and promotes endogenous technical change (Morrissey, 2001).
Papanek (1973), in a cross–country regression analysis of 34 countries in the 1950s and 51 countries
in the1960s, treating foreign aid, foreign investment, other flows and domestic savings as
explanatory variables, finds that foreign aid has a substantially greater effect on growth than the
other variables. He explains that "aid, unlike domestic savings, can fill the foreign exchange gap as
well as the savings gap. Unlike foreign private investment and other foreign inflows, aid is supposed
to be specifically designed to foster

Hausman, Autocorrelation Test and Heteroscedasticity,...
Hausman test
Hausman test which usually accepted method of selecting between random and fixed effects which
is running on regression equation. Hausman (1978) provided a tectonic change in interpretation
related to the specification of econometric models. The seminal insight that one could compare two
models which were both consistent under the null spawned a test which was both simple and
powerful. The so–called 'Hausman test' has been applied and extended theoretically in a variety of
econometric domains. We focus on the construction of the Hausman test in a variety of panel data
settings, and in particular, the recent adaptation of the Hausman test to semi–parametric and
nonparametric panel data models. A formal application of the Hausman test is given focusing on
testing between fixed and random effects within a panel data model. Mostly fixed effects are
accepted way to run with panel data as they always present consistent outcomes but may not be the
most effective way to implement. On the other hand, random effects usually provide to the
researcher better P–values as it considered to be a more active estimator, so researcher can study
random effects if it is reasonable to do so. Moreover, Hausman test choose a more effective model
compared to a less efficient as consistent model should presents robust estimates and consistent
results owing to the more efficient model.
Autocorrelation test
Another terms sometimes used for describe Autocorrelation these are "lagged

What Is The Methodology Used In Costimating The Impact Of...
This section gives and explains the methodology that is going to be used in estimating the impact of
capital flight on economic growth in Zimbabwe for the period 1980 to 2015. This encompasses the
specification of the model but no specific theory can be attributed to the selection of variables to be
used. Model diagnostic tests are to be conducted before interpretation of estimated results of the
correctly specified model. 3.0Methodology There are quite number of methods of estimating
regression functions, the generally used ones being the ordinary least squares (OLS) and the
maximum likelihood (ML). This paper will use (OLS) over (ML) because of the properties of (OLS)
that is its ability to produce best linear unbiased estimate thus ... Show more content on
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3.2 Stationarity Test Testing the stationary properties of time series is a very important exercise as
the use of stationary time series data in the Classical Linear Regression Model will result in inflated
results. The results are likely to be inconsistent and with a low Durbin Watson (DW) statistic.
Several methods can be employed to test whether the time series variables are stationary , these
includes residual plot but this paper will employ the Augmented Dickey Fuller (ADF) to test the
existence of a unit root. Conclusion of stationarity is going to be considered at 1% and 5% level of
significance only. Any probability of each variable below the two values will be considered
stationary. If the model fails to meet the stationary requirement, we will use the differencing method
to make our model stationary. 3.3 Model Diagnostic Tests Multicollinearity is a test to assess the
randomness of explanatory variables. They are other tests which include the Auxiliary Regressions
and correlation matrix. This study will consider pair wise correlation coefficient from the correlation
matrix. If the pair–wise or zero–order correlation coefficient between two explanatory variables is
high, say in excess of 0.8, then multicollinearity is a serious problem (Gujarati, 2004: 359). In the
case that two variables are highly correlated then one of it must be dropped. For

Research Report On Data Collection
3.1 INTRODUCTION
In this chapter, the focus is on the methodology used in the study. It include the data collection, data
source, variables, research design, theoretical research framework, sampling design, test
consideration for data analysis, hypotheses statement and conclusion.
3.2 DATA COLLECTION
Data collection involves the process of gathering information and data either from primary or
secondary data. In this study only secondary data is used.
3.2.1 Secondary Data
Secondary data refers to the statistical material which is obtained from someone else records.
Secondary data helped researcher's understanding so as to define problem, formulate research design
and interpret the results. This type of data is generally taken from sources ... Show more content on
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The values can differ at various times for the same objects or person. The variables consist of
dependent and independent.
3.3.1 Dependent Variable
The dependent variable is denoted as variable of primary interest to the researcher as it provides a
measurement of the effect of the independent variables. In this research, foreign direct investment
(FDI) is the designated dependent variable where it indicates the outcome of the change brought
about by changes in the independent variables.
3.3.2 Independent Variables
Independent variables (predictor variables) are the ones that influence the dependent variable and
they explain the variance in dependent variable. In this research, gross domestic product (GDP),
interest rate (IR), exchange rate (ER), inflation rate (IFR), unemployment rate (UR), company tax
(CT) and labour cost (LC) are the independent variables that were used to

Econometrics Project
INTRODUCTION LITERATURE REVIEW The current economic crisis has become a major
concern of all nations today. It has led policymakers and economists to rethink about the instrument
for economics stability. One of the most damaging consequences of this crisis is the consumption
instability, which negatively affects risk adverse agents' welfare. As mentioned by Athahasoulis and
van Wincoop (2000) as well as Pallage and Robes (2003), consumption instability could have
detrimental consequences for the accumulation of human capital and physical capital. Therefore, the
study of the relationship between the economic indicators such as household consumption, GDP
growth, GNI per capita and inflation rate is necessary and important in order to ... Show more
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Yi: Gross national income per capita (measured in US dollar). It can be defined as the sum of value
added by all resident producers plus any product taxes (less subsidies) not included in the valuation
of output plus net receipts of primary income (compensation of employees and property income)
from abroad. In this model, we want to observe if gross national income per capita has a significant
effect on total private domestic consumption as a percentage of GDP. If gross national income per
capita increases, total private domestic consumption as a percentage of GDP is expected to increase
because a rise in income encourages households to spend and consume more. Thus, β3 is expected
to be positive. The data for this variable were obtained from this site –
http://data.worldbank.org/indicator/NY.GNP.PCAP.PP.CD/countries 3. Ii: Annual inflation rate
(measured in %). Inflation rate, as measured by the consumer price index, reflects the annual
percentage change in the cost to the average consumer of acquiring a basket of goods and services
that may be fixed or changed at specified intervals, such as yearly (as employed in this research
paper). In this model, we want to observe if annual inflation rate has a significant effect on total
private domestic consumption as a percentage of GDP. If annual inflation rate increases, total private
domestic consumption as a percentage of GDP is expected to decrease because inflation implies a
rise in the general level

Factor Affecting Performance of Stock Market
Abstract
This study examines the effects of foreign direct investment, market capitalization and adjusted on
stock market using time series data from 1991 to 2011. A result shows that there is a significant
relationship between foreign direct investment and stock market, as well as there is also a significant
relationship between adjusted saving and stock market but there is insignificant relationship between
market capitalization and stock market. Foreign direct investment, Market capitalization and
Adjusted saving explains 90% of variation in the stock market. It is recommended that the
government can encourage FDI in Pakistan to increase its savings by taking various steps provide
incentives and save foreign investors interest in a ... Show more content on Helpwriting.net ...
The results have shown positive statistically strong relationship between FDI and market
capitalization thus reflecting the complementary role of FDI in the stock market development of
Pakistan. Raza et al. (2012) investigated the role of foreign direct investment in developing host
country's stock markets and to examine whether they are related or not. The results disclosed a
positive impact of foreign direct investment along with other explanatory variables in developing
Stock markets of Pakistan.
Adam and Tweneboah (2008) analyzed the impact of Foreign Direct Investment (FDI) on stock
market development in Ghana. Market capitalization, FDI, stock market development and exchange
rate variable are considered and found long–run relationship between FDI and stock market
development in Ghana. Raza and Jawaid (2012) investigated the effects of foreign capital inflows
and economic growth on stock market capitalization in 18 Asian countries by using the panel data
from the period of 2000–2010 and found that foreign direct investment has significant negative and
economic growth has significant positive relationship with the stock market capitalization, whereas,
the results of workers' remittances is found insignificant in long run. However, no causal
relationship is found in between workers' remittances and stock market capitalization. They
suggested that investor should not idealize the inflow of workers' remittances to

Econometric Analysis of Capm
Prepared by: Lok Kin Gary Ng, contact email: gary_ng_@hotmail.com May, 2009 School of
Economic Introduction The analysis of this paper will derive the validity of the Fama and French
(FF) model and the efficiency of the Capital Asset Pricing Model (CAPM). The comparison of the
Fama and French Model and CAPM (Sharpe, 1964 & Lintner, 1965) uses real time data of stock
market to practise its efficacy. The implication of the function in realistic conditions would justify
the utility of the CAPM theory. The theory suggests that the expected return demanded by investors
on a risky asset depends on the risk–free rate of interest, the expected return on the market portfolio,
the variance of the return on the market portfolio, and ... Show more content on Helpwriting.net ...
Hence, Fama & French's three factor model flourished when considering the market book value and
the size of business. Additionally, in Fama and French's (1996) paper, they concluded Sharpe –
Lintner's CAPM has never been an empirical success. According to the current study, the factors that
affected the Beta are serious enough to invalidate most applications of the CAPM Even though there
are flaws in the CAPM for empirical study, the approach of the linearity of expected return and risk
is readily relevant. As Fama & French (2004:20) stated "... Markowitz's portfolio model ... is
nevertheless a theoretical tour de force." It could be seen that the study of this paper may possibly
justify Fama & French's study that stated the CAPM is insufficient in interpreting the expected
return with respect to risk. This is due to the failure of considering the other market factors that
would affect the stock price. Specification of model The primary estimated model is presented as;
rprft = α0 + β1(rmrf)t + β2(smb)t + β3(hml)t + εt This FF three factor model is derived from the
CAPM (Peirson et al, 2007); E(Rp)t – Rft = (1(E(Rm) –Rf)t Given that; (i = Cov(Rp,Rm) = risk
factor on the portfolio with respect to the market. ((m)2 This leads to the secondary estimated
model, this can be rewritten as; rprft = (0t +(1(rmrft) + εt Under both of these models; Assume a
common pure rate of interest, with all

Forecasting By Vector Autoregression Models
CHAPTER NINE
FORECASTING BY VECTOR AUTOREGRESSION MODELS
9.1 Vector Autoregressive (VAR) Models
Vector Autoregression (VAR) models were introduced by the macro– econometrician Christopher
Sims (1980) to model the joint dynamics and causal relations among a set of macroeconomic
variables. The vector autoregression (VAR) is commonly used for forecasting systems of interrelated
time series and for analyzing the dynamic impact of random disturbances on the system of variables.
The VAR approach sidesteps the need for structural modeling by treating every endogenous variable
in the system as a function of the lagged values of all of the endogenous variables in the system.
The vector autoregression (VAR) model is one of the most successful, flexible, and easy to use
models for the analysis of multivariate time series. It is a natural extension of the univariate
autoregressive model to dynamic multivariate time series. The VAR model has proven to be
especially useful for describing the dynamic behavior of economic and financial time series and for
forecasting. It often provides superior forecasts to those from univariate time series models and
elaborate theory–based simultaneous equations models. Forecasts from VAR models are quite
flexible because they can be made conditional on the potential future paths of specified variables in
the model.
In addition to data description and forecasting, the VAR model is also used for structural inference
and policy analysis. In structural

The Effect Of Effect On Emerging Stock Markets Of Four...
Part 3 – Data and Methodology
3.1 Data Description The purpose of this study is to investigate the presence of January effect in
emerging stock markets of four Southeast Asia countries: Malaysia, Thailand, Philippine and
Indonesia, for the period of January 2012 until December 2015, which is the most recent period after
the financial crisis in 2007–2008. The financial crisis would affect the behaviour of the stock
markets and thus the stock price might not reflect its true value. As the most recent economic crisis
is believed to have ended in Fall 2011 (Elliott 2011; Weisenthal 2013), this study will focus on the
most recent 4–year period, from January 2012 until December 2015. The four Southeast Asia
countries are selected because there are limited studies about them. Furthermore, they are the only
Southeast Asia countries being included in MSCI Emerging Markets Index as of 2016. Thus it is
worth examining the efficiency of the stock markets of these high growth emerging markets.
Daily equity market indices for four Southeast Asia countries will be collected from Yahoo Finance
and DataStream. The daily price index is collected instead of monthly price index because this study
attempts to examine if the January effect is stronger on the first five days of January. The indices are
FTSE Bursa Malaysia KLCI Index (KLCI) for Malaysia, SET Index for Thailand, Philippine Stock
Exchange Composite Index (PSEi) for Philippine and IDX Composite Index for Indonesia. Since
these

Relationship Between Vietnamese Stock Price Relative On...
METHODLOGY
The purpose of this paper is concentrated on relationship between Vietnamese stock price relative to
exchange rate and United State stock market. In order to have a better view about this relationships,
the suitable econometrics model will be used in the research are OLS and ARMA. To determine the
correlation, coefficients among the variables from the test we will be able to find out the β, R2, P–
value, Standard Error, Durbin–Watson stat statistic etc... With the time series dataset, in other to get
a good forecast, the regressions will be run and tested on EVIEW program. The main model will be
use is:
VNSP= β_0 + β_1S&P500 + β_2VNER + ε (e1)
By using OLS model we can determine how much the dependent variable is influenced by the
independent variables. The null and alternative hypothesizes will be as following:
VNSP Viet Nam's monthly stock price index β Beta
S&P500 American monthly stock market index
VNER Viet Nam's monthly exchange rate ε Error term
H_0: The Viet Nam's monthly stock price index is not influenced by American monthly stock
market index and Viet Nam's monthly exchange rate.
H_1: The Viet Nam's monthly stock price index is influenced by American monthly stock market
index and Viet Nam's monthly exchange rate.
MODELS
The program will be used to run regressions and analyze the outputs is EVIEW8. The Least Squares
method of estimation is used for the analysis of the data. The least squares method of estimation is
preferred

Determinants of Fdi in Saudi Arabia
FOREIGN DIRECT INVESTMENT IN SAUDI ARABIA–AN ECONOMIC DEVELOPMENT
PERSPECTIVE
Khalid Alkhathlan, Department of Economics, King Saud University, Riyadh, KSA
Md.Tarique, College of Business Administration, Al–Kharj, King Saud University, Riyadh, KSA.
ABSTRACT
Foreign Direct Investment (FDI) plays an important role in stimulating the growth potentials and
providing stability to the economy of Saudi Arabia. Our findings show that there are mainly four
factors which determine the net FDI flow to Saudi Arabia. These are – GDP, Privatization, Import
and Export and Growth rate of GDP. There exists a positive relationship between FDI and GDP and
GDP growth rate while it is negatively related to privatisation and imports plus exports taken ...
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The third segment is devoted to the discussion of factors affecting FDI. The methodology of the
study is described in fourth section. The fifth section provides the details of the results and final
section presents the main conclusions and recommendations.
2. LITERATURE REVIEW
Estimates reported by the European Bank for Reconstruction and Development (EBRD,1997)
suggest that several countries have experienced very rapid growth of the private sector during the
transition period. A number of studies have suggested that investment and growth in developing
economies is positively associated with indicators of 'openness' and export promotion
(Balasubramanyam et al., 1996). Such findings may suggest that investors prefer countries with
relatively liberal trade regimes and few constraints on profit repatriation, possibly within regions
with wider supra–national free trade arrangements. De Mello (2000) analyzed the time series and
panel data for 32 OECD and non–OECD countries for the period 1970–90. He estimated the impact
of FDI on capital accumulation and output growth in the recipient economy supporting the FDI led
growth hypothesis. Similarly, Soto (2000); Alfaro, Chanda, Kalelmi–Ozcan, Sayek (2004); Li and
Liu (2005) found positive impact of FDI on GDP growth. They all used FDI measure as percentage
of GDP. Liu et al. (2002) examined the long–run relationship between economic growth, FDI and
trade in China. A study on the quarterly data for imports,

Pengaruh Tingkat Bagi Hasil Dan Suku Bunga Terhadap...
Pengaruh Tingkat Bagi Hasil Dan Suku Bunga Terhadap Simpanan Mudharabah (Studi Kasus BPR
Syariah Bangun Drajat Warga Yogyakarta) Periode Tahun 2002 – Tahun 2005 SKRIPSI Oleh: Nama
: Erik Rio Indrawan Nomor Mahasiswa : 02.313.032 Program Studi : Ekonomi Pembangunan
UNIVERSITAS ISLAM INDONESIA FAKULTAS EKONOMI YOGYAKARTA 2006
Pengaruh Tingkat Bagi Hasil Dan Suku Bunga Terhadap Simpanan Mudharabah (Studi Kasus
BPR Syariah Bangun Drajat Warga Yogyakarta) Periode Tahun 2002 – Tahun 2005 SKRIPSI
disusun dan diajukan untuk memenuhi syarat ujian akhir guna memperoleh gelar Sarjana jenjang
strata 1 Program Studi Ekonomi Pembangunan, pada Fakultas Ekonomi Universitas Islam Indonesia
Oleh : Nama Nomor Mahasiswa Program Studi : Erik Rio ... Show more content on Helpwriting.net
...
Maksud penyusunan skripsi ini adalah sebagai salah satu syarat untuk menyelesaikan program
pendidikan Strata Satu (S–1) pada Fakultas Ekonomi Jurusan Ilmu Ekonomi Studi Pembangunan
Universitas Islam Indonesia. Dengan selesainya penyusunan skripsi ini penulis menyampaikan
terima kasih yang sebesar–besarnya kepada Dra. Sarastri mumpuni R, M.Si. selaku Dosen
Pembimbing Skripsi, yang telah banyak meluangkan waktunya yang berharga dalam memberikan
pengarahan, bimbingan, petunjuk ataupun motivasi kepada penulis dalam menyelesaikan
penyusunan skripsi ini. Dalam kesempatan ini tidak lupa penulis ingin menyampaikan ucapan
terima kasih kepada semua pihak yang telah membantu dalam penyusunan skripsi ini, terutama
kepada: vii 1. Drs. Asmai Ishak, M.Bus, Ph.D. selaku Dekan Fakultas Ekonomi Universitas Islam
Indonesia. 2. Drs. Jaka Sriyana, M.Si. selaku Ketua Jurusan sekaligus penguji skripsi, yang telah
memberikan motivasi dan petunjuk. 3. Drs, Priyonggo Suseno, M.Sc.selaku penguji skripsi, terima
kasih atas segala koreksi terhadap penulis. 4. Drs. Eko Atmaji, M.Ec. selaku Dosen Pembimbing
Akademik, yang telah memberikan pengarahan, motivasi dan petunjuk bagi penulis. 5. Segenap
dosen dan karyawan Fakultas Ekonomi Universitas Islam Indonesia atas asuhan,bimbingan, dan
bantuan yang diberikan selama masa perkuliahan. 6. Kedua orang tuaku, papi dan mami tersayang
yang tak

Regression Analysis of Dependent Variables
Table: 1, represents the results of regression analysis carried out with the dependent variables of
cnx_auto, cnx_auto, cnx_bank, cnx_energy, cnx_finance, cnx_fmcg, cnx_it, cnx_metal,
cnx_midcap, cnx_nifty, cnx_psu_bank, cnx_smallcap and with the independent variables such as
CPI, Forex_Rates_USD, GDP, Gold, Silver, WPI_inflation. The coefficient of determination,
denoted R² and pronounced as R squared, indicates how well data points fit a statistical model and
the adjusted R² values in the analysis are fairly good which is more than 60%, indicates the
considered model is fit for analysis. Also, the F–Statistics which provides the statistical significance
of the model and its probabilities which are below 5% level and hence proves the model's
significance.
Table: 1: Regression Results.
Method: Least Squares
Sample: 2005Q1 2013Q4
Included observations: 36
R–squared Adjusted R–squared F–statistic Prob(F–statistic)
0.955378 0.946146 103.4845 0.00000
0.963182 0.955564 126.4426 0.00000
0.746736 0.90889 15.58318 0.01877
0.952115 0.942208 96.10377 0.00000
0.960883 0.95279 118.7272 0.00000
0.868418 0.841194 31.89909 0.00000
0.87641 0.85084 34.27454 0.00000
0.933336 0.919543 67.66915 0.00000
0.889215 0.866294 38.79462 0.00000
0.924163 0.908473 58.89987 0.00000
0.739903 0.68609 13.74949 0.00000
Serial Correlation and Heteroskedasticity:
Normally the possibilities for the time series data to have the Serial correlation or auto correlation
are more. It can be tested with the

Variables Of The Working Capital Requirements Essay
Dependent variables
1– working capital requirement ( WCR )
The study observes the determinants of the working capital requirements of an enterprise. Working
Capital Requirements (WCR_TA) were included as a dependent variable, as used by Shulman and
Cox (1985), as a measure of working capital management (cash and equivalents + marketable
securities + inventories + accounts receivables) – (accounts payables + other payables). Working
capital requirements are deflated by total assets to control the size effect
2– Cash Conversion Cycle (CCC)
Cash Conversion Cycle (CCC) as a measure of working capital management, where a shorter CCC
represents the aggressiveness of working capital management measured by the following Cash
Conversion Cycle = Inventory days + Accounts Receivables days – Accounts Payable day
Independent Variable Measures:
1– Operating cash flows deflated by total assets (OCF_TA) the cash flows generated from the
routine operations of the enterprise and obtained directly from the cash flow statement as well as
deflated by total assets. The high value of this ratio shows that the enterprise main operation
generating enough cash this also decreasing operation risk.
2– Size
The Size ratios generally measure the enterprise dimensions about the age i.e. for how many years'
enterprise start business also measuring enterprise size and annual growth this dimensions are very
important because it is affecting the decision related to policy of managing

Using Stata for Principles of Econometrics
Using Stata For Principles of Econometrics . Third Edition I ·1· I ! t . i: f, I Lee Adkins dedicates
this work to his lovely and loving wife, Kathy , Carter Hill dedicates this work to Stan Johnson and
George Judge – ' , . Bicentennial Logo Design: Richard 1. Pacifico Copyright @ 2008 John Wiley &
Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval
system or transmitted in any form or by any means, electronic, mechanical, photocopying,
recording, scanning, or otherwise, exC;ept as permitted under Sections 107 or 108 of the 1976
United States Copyright Act, without either the prior written permission of the Publisher, or
authorization through payment of ... Show more content on Helpwriting.net ...
2.4:1 Fitted values and residuals 63 2.4.2 Computing an elasticity 65 2.4.3 Plotting the fitted
regression line 67 2.4.4 Estimating the variance of the error term 70 2.4.5 Viewing estimated

Crime Rates: an Econometric Analysis
Crime Rates: An Econometric Analysis using population, unemployment and growth Table of
Contents I. Introduction A.) Background of the Study B.) Problem Statement C.) Objectives D.)
Significance of the Study E.) Scope and Limitations II. Review of Related Literature III.
Operational Framework A.) Variable List B.) Model Specification C.) A–priori Expectations IV.
Methodology A.) Data B.) Preliminary Tests V. Results and Discussions VI. Conclusion and
Recommendations VII. Bibliography VIII. Appendices INTRODUCTION A. Background of the
Study Ever since the first civilizations, ever since the dawn of government and morals, crime has
accompanied mankind in his everyday ... Show more content on Helpwriting.net ...
The researcher would have preferred to add potential influences such as literacy rates and family
incomes however such data are collected in periods of 3 years or greater, thus leaving the researcher
no choice but to analyze based on annually recorded economic variables. REVIEW OF RELATED
LITERATURE Prior to 1968, crime was viewed as a social and moral construct. However this
changed when Gary Becker's Crime and Punishment: An Economic Approach was published in
1968. Becker takes into account the Opportunities and Costs of committing a crime; that a criminal
would steal because the benefits are greater than the costs. Wadsworth (2001), on the other hand,
states that employment is a key factor that affects crime rates. It is not the fact of unemployment that
pushes them into being criminals but the hardships that they experience. The ideals in this study will
follow suite to the ideals of the said researchers. The variables of CPI, Income, unemployment and
population density all play important roles in determining crime rates. OPERATIONAL
FRAMEWORK A. Variable List The variables used in the model are described as follows: Variable
Name | Description | Lncrimerate | Crime Rate | d_l_gnipc | Gross National Income Per Capita |
d_l_urbanpop | Population in Urbanized Areas | d_l_cpi | Consumer Price Index | d_l_popdens |
Population Density | d_l_unemp | Number of Unemployed Persons | B. Model

Forecasting Using Eviews
Data The variables of interest are oil imports to Germany, and temperature in Germany. The latter is
used as a leading indicator for the former, to improve on the forecast obtained by the univariate
model. Both variables are collected over a time range from January 1985 until and including
December 1997, whereas the last year is not used for constructing the optimal forecast, obtained by
fitting a model through the data until the end of 1996. This will enable us to forecast the year 1997
using our model, and then comparing it to the actual data. Assuming no large one time shock,
meaning that it is not captured by seasonality or cyclical behaviour in the data, occurs in this year, a
graphical comparison of our forecast and the whole data ... Show more content on Helpwriting.net ...
The insignificant December month can be explained by the little temperature difference compared to
the base month January, and roughly the same oil is consumed therefore. Moreover the negative
signs of their coefficients are in line with intuition, that in the coldest month January more oil is
needed than in all the other month. The last step before fitting autoregressive and moving averages
terms to the data, is to check for unit roots. We will use the augmented Dickey–Fuller test to decide
whether the data has a unit root or not. The H0 of the test is that the data has a unit root against the
Ha, that the data has no unit root. Table 1.1 shows the result of the augmented Dickey–Fuller test.
The p–value of the

Notes On The Law Of Demand
Question 1
1. Identify the Research Question: In this case being the Law of Demand, which postulates that
quantity demanded is negatively related to price, that is to say, and increase in price decreases
quantity demanded.
2. Economic Model: The economic model can be stated as Qd = f (P,Y), where P is the price of the
good, and Y is the income of the person.
3. Econometric Model: The econometric model can stated as QD = α + β1 (P) + β2 (Y) + ɛ, where β
are the estimated coefficients, α is the constant term, and ɛ is the stochastic error term.
4. Collecting Data and Defining Variables: We gather data on quantity demand for a good, the price
of a good, and the incomes for all the consumers, for example on a yearly basis.
5. Inspect and ... Show more content on Helpwriting.net ...
The value of b2 is 0.724097. b2 is related β2, since b2 is the estimated coefficient value, and β2 is
the to be estimated parameter.
Part C.
The goodness of fit of the model, or how well the estimates fit the model is defined by the R2 value,
which is 0.90, meaning 90 percent of the data has been accommodated by the model.
Part D.
The additional variables could include, Years of Work Experiences, Ethnicity, Gender, Inflation, and
Unemployment. According to economic theory, wage is assumed to be a positive function years of
work experience and inflation; and a negative function of unemployment. Ethnicity and Gender are
neutral in relationships, as they would be used to highlight if wages are gender or ethnicity bias.
Through the inclusion of more independent variables, there are two effects on the regression
analysis, 1) Parsimony, par simonious models are superior to less parsimonious ones, assuming
other things being equal. However, there 's always the question of just how parsimonious a model
should be; 2) Over–fitting, which can result in increased R2.
Question 3

Part A.
At 1 percent significance level, and 21–2=19 degrees of freedom, the critical values are are given as
+/– 2.860. Since the t–ratio for price is –3.5869, which is greater than

What Is The Stakeholder Theory Of Agency Theory
Agency theory
It is an acknowledged fact that the principal–agent theory is generally considered the starting point
for any debate on the issue of corporate governance emanating from the classical thesis on The
Modern Corporation and Private Property by Adolf Berle and Gardiner Means. According to this
thesis, the fundamental agency problem in modern firms is primarily due to the separation between
finance and management. Modern firms are seen to suffer from separation of ownership and control
and therefore are run by professional managers (agents) who cannot be held accountable by
dispersed shareholders. This separation of ownership from management and the resulting loss of
direct owner involvement in the firm forced many people to rethink the conventional wisdom about
the role of markets and the need for private ownership of capital in shaping ... Show more content
on Helpwriting.net ...
By expanding the spectrum of interested parties, the stakeholder theory stipulates that, a corporate
entity invariably seeks to provide a balance between the interests of its diverse stakeholders in order
to ensure that each interest constituency receives some degree of satisfaction (Abrams, 1951). The
stakeholder theory is therefore appears better in explaining the role of corporate governance than the
agency theory by highlighting the various constituents of a firm. Thus, creditors, customers,
employees, banks, governments, and society are regarded as relevant stakeholders. Related to the
above discussion, John and Senbet (1998) provide a comprehensive review of the stakeholders'
theory of corporate governance which points out the presence of many parties with competing
interests in the operations of the firm. They also emphasize the role of non–market mechanisms such
as the size of the board, committee structure as important to firm

Distributed Lag Model For Money Supply And Price...
CHAPTER EIGHT DISTRIBUTED LAG MODEL FOR MONEY SUPPLY AND PRICE
RELATIONSHIP 8.1 Distributed Lag Model The economic variable Y is affected by not only the
value of X at the same time t but also by its lagged values plus some disturbance term i.e.X_t,X_(t–
1),X_(t–2).....,X_(t–k),ε_t.this can be written in the functional form as: 〖Y_t=f(X〗_t,X_(t–
1),X_(t–2).....,X_(t–k),ε_t) In linear form, Y_t=α+β_0 X_t+β_1 X_(t–1)+β_2 X_(t–2)+⋯+β_j X_(t–
k)+ε_t (8.1) Where, β_0 is known as the short run multiplier, or impact multiplier because it gives
the change in the mean value of Y_t following a unit change of X_tin the same time period. If the
change of X_t is maintained at the same level thereafter, then, (β_0+β_1) gives the change in the
mean value of Y_t in the next period, (β_0 + β_1+β_2) in the following period, and so on. These
partial sums are called interim or intermediate multiplier. Finally, after k periods, that is =β,
therefore ∑▒β_i is called the long run multiplier or total multiplier, or distributed–lag multiplier. If
we define the standardized β_i^* = β_i/(∑▒β_i ) then it gives the proportion of the long run, or total,
impact felt by a certain period of time. In order for the distributed lag model to make sense, the lag
coefficients must tend to zero as k. This is not to say that 2 is smaller than 1; it only means
that the impact of X_(t–k)on Y_t must eventually become small as k gets large. The distributed lag
plays

Trade Openness and Economic Growth in Nigeria
CHAPTER ONE INTROUDCTION 1.1 BACKGROUND OF STUDY The current period in the
world economy is regarded as period of globalization and trade liberalization. In this period, one the
crucial issues in development and international economics is to know whether trade openness indeed
promotes growth. With globalization, two major trends are noticeable: first is the emergence of
multinational firms with strong presence in different, strategically located markets; and secondly,
convergence of consumer tastes for the most competitive products, irrespective of where they are
made. In this context of the world as a "global village", regional integration constitutes an effective
means of not only improving the level of participation of countries in ... Show more content on
Helpwriting.net ...
This is approximately US 8.2 per month or US 27 cents per day. Doug Addison (unpublished)
further explained that the Nigeria economy is not merely volatile; it is one of the most volatile
economies in the world (see figure 1 below). There is evidence that this volatility is adversely
affecting the real growth rate of Nigeria's gross domestic product (GDP) by inhibiting investment
and reducing the productivity of investment, both public and private. Economic theory and
empirical evidence suggest that sustained high future growth and poverty reduction are unlikely
without a significant reduction in volatility. Oil price fluctuations drive only part of Nigeria's
volatility policy choices have also contributed to the problem. Yet policy choices are available that
can help accelerate growth and thus help reduce the percentage of people living in poverty, despite
the severity of Nigeria's problems. Figure 1: growth rate of real GDP Nigeria real GDP Growth Rate
During the period 1960–1997, Nigeria's growth rate of per capital GDP of 1.45% compares
unfavorably with that reported by other countries, especially those posted by china and the Asian
Tigers such as Hong Kong, Singapore, Taiwan, and south Korea, viewed in this comparative
perspective, Nigeria's per capita income growth has been woefully low and needs to be improved
upon.

A Report On Engle Granger Cointegration Test
4. Empirical Results In this section, we discuss our findings of Engle–Granger cointegration test
which we applied in order to identify whether there is cointegration relationship between dependent
variable – the real non–oil GDP and independent variables – real credit to the private sector and
non–oil sector real effective exchange rate. The steps of the EG approach have been undertaken in
order to obtain the long–run model that explains the relationship between these variables. 4.1. Unit
Root Test First of all, variables should be given in log levels in order to alleviate the problem of
serial correlation and the elasticity of the coefficients. The results of ADF unit root test in levels
concludes that all three variables – seasonally ... Show more content on Helpwriting.net ...
Table Variable name ADF test (1% critical value =–3.557472, N=56), H0: [has a unit root] Inference
t–Statistic Prob.* ln_rgdp_noil_sa –0.202877 0.9314 I(1) ln_rcred_to_ps –0.874036 0.7892 I(1)
ln_reer_noil –0.507243 0.8815 I(1) 5% critical value =–3.557472, N=55, t=0 d(ln_rgdp_noil_sa) –
11.60110 0 I(0) d(ln_cred_to_ps) –9.090784 0 I(0) dln_reer_noil) –5.649022 0 I(0) Sample:
2000Q1:2013Q4 In the Table , d stands for 1st difference, such that d(ln_rgdp_noil_sa) is the result
of the 1st difference ADF unit root test on seasonally adjusted real non–oil GDP and etc. The graphs
below show the trend of the three series through the period from 2000 to 2013 based on level and
1st difference Augmented Dickey Fuller unit root tests, respectively. Figure Figure ADL and
Optimal Lag Selection: From General to Specific After checking for stationarity, autoregressive
distributed lag (ADL) models are estimated and the proper lag length is chosen so as to make the
residuals of our model white noise. As can be seen in the tables on ADLs in Appendix 1, all the
model specifications' residuals according to the Jarque–Bera Histogram–Normality tests, Breusch–
Godfrey serial correlation LM tests, and Breusch–Pagan–Godfrey Heteroskedasticity tests are
normally distributed, serially uncorrelated and homoscedastic, respectively. It shows that all residual
diagnostic parameters are satisfactory for estimating our model. Therefore, the

The Net Inflow Of Fdi Into The Developing Countries
Sample Data
Figure 1 shows the net inflow of FDI into the developing countries. There is a fall into the amount
of FDI going to the developing countries from late 1980 to early 1990 and in the late 2000. Overall,
there is an upward trend of amount of FDI going to the developing countries. The same trend with
ODA shown in Figure 2. The amount of Net ODA received by developing countries from 1990 to
mid–1990 is fluctuating then continued to fall until 2000. From year 2000 onwards, there is a steady
increase of ODA received by the low–income countries. Compared with FDI and Net ODA,
personal remittances has a steady upward trend (shown in Figure 3), noting a huge increase in 2008
of US$4.5 billion from US$15.2 billion in 2007. With the ... Show more content on Helpwriting.net
...
The independent variables (all are current U.S. dollars) are FDI defined as sum of equity capital,
reinvestment of earnings, other long–term capital, and short–term capital as shown in the balance of
payments less disinvestment; Net ODA consists of net repayments of principal and grants by
Development Assistance Committee members agencies and by non–DAC countries to promote
economic development; and personal remittances is consists of personal transfers (all current
transfers between resident and non–resident individuals) and compensation of employees (income of
workers who are employed in foreign country).
Descriptive statistics in Table 3 employed the logarithmic function of the variables as suggested by
the reference literatures and thus will also use in the regression analysis. It shows that among
variables, there are different observations due to in some years, data is not given. This also somehow
affect the deviation of variables from the mean. LogFDI and LogRem have the highest deviations
from the mean which are 2.59201 and 2.393887 respectively. The average amount of FDI low–
income countries received increases by 17.00671% annually, and the lowest percentage increase
2.374347%. For Net ODA, countries have an average of 19.69657% increase in the amount they
received annually and the percentage increase could be high as 22.43425%. In the case of personal
remittances, low–income countries received an average increase of 17.47987% and the highest
increase could

The Housing Bubble And The Gdp : A Correlation Perspective
LITERATURE REVIEW A study from Ray M. Valadez, "The housing bubble and the GDP: a
correlation perspective" in Journal of Case Research in Business and Economics has been done to
focus on the relationship between the Real Gross Domestic Product and the situation of Housing
Bubble. In this research, the author has concentrated on the time from the beginning of losing trust
in government from the financial institution. He emphasizes how much the housing bubble relates to
the recession in the economy. The author takes the sample on changes in GDP and changes in the
housing price index from 2005 to 2006 in order to illustrate the statistical connection between them.
The dependent variable were used is quarterly changes of adjusted GDP, the database of the research
were base on a report on NCSS software. According these results, the changes in both HPI and GDP
have likely similar common from in the period of 2005 and 2006, the data showed that there were
significant changes in the next two years. The result also showed that housing price and GDP has
been long observed and their relationship has more innovations at the end of 2009. Another
Research has done by a group of composers including Zhuo Chen, Seong–Hoon Cho, Neelam
Poudyal and Roland K. Roberts. The name of research was "Forecasting Housing Prices under
Different Submarket Assumptions." The paper focus on the submarket and use the data of home
sale. The database was taken from the Knoxville city combined with

Relation Between Stock Returns And Economic Growth
Many investors when making a decision regarding investing in a other country take into account
certain factors which may play a very important role or may affect their future returns. Standard
economics theory suggests that over the long run, profits or returns should rise in line with the
economy/ economic growth, which is also the view point of many investors when making a
decision.
Although the long run research and studies conducted by different economists gives a very different
picture of the relationship between stock returns and economic growth, but very little empirical
evidences to support the view with. Many economists and researchers supported the view that, stock
returns and economic growth does not have a positive ... Show more content on Helpwriting.net ...
Jay.R Ritter in his research said that the main reason for a negative correlation between the two
factors, according to him during high growth rate periods markets usually assign a high
price/Earning and price to dividend multiples and which then lowers the realized returns because
now more capital is required from the investors to in order to receive the same level of earning s and
dividends from stocks.
From all these studies and empirical evidence it can be concluded that stock returns and economic
growth are not related but have a negative correlation.
Ho= no correlation between economic growth and stock return.
H1= there is a relation between economic growth and stock returns
On the other hand the results for interest rates give the same type of results. The basic classical
economics model suggests that there is a relationship between interest rates and economic growth.
Usually reduction in the interest rates cause the level of growth to increase, this is because a
reduction in interest rates makes borrowing more cheaper and encourages in investment in the
economy, which eventually increases the growth rate. However, an increase in interest rates has an
opposite effect on economic growth. According to (Suntum, 2008) high interest rated discourage
investment as it's more tempting to rather save the money and earn a decent interest rate, thus
making the aggregate demand to fall which then badly affects the economic growth of

Which Model For Forecasting Of Nepalese Inflation Is...
A. RESEARCH QUESTIONS
– Which model for forecasting of Nepalese inflation is suitable?
– Is Nepalese inflation caused by inflow of remittance along with the population growth and
political instability in Nepal ?
– Do the money supplies affect price level/inflation in Nepal? If yes, then at what extent money
supplies affect Nepalese price level?
– Does the relationship between Ms & P hold QTM in Nepal?
– Is there any SR & LR relationship between Ms & P?
– Is the relationship between Ms & P robust and stable?
B. BRIDGING RESEARCH GAP
– Impact of remittance along with population growth and political instability.
– Intensive study on the relationship between Ms & P employing variety of tools.
– Confirmation of the relationship between Ms & P applying various diagnostic tests.
– Generalization is made on the basis of not only the single test but on the basis of a number of tests.
C. OBJECTIVES
I. GENERAL OBJECTIVE To explore and examine the state of the relationship between Ms & P in
the line of QTM.
II. SPECIFIC OBJECTIVE
– Identify the suitable model of inflation forecasting
– Examine the impact of remittance on inflation
– Examine the relationship between Ms & P and extent of relationship by ARDL models.
– Analyze the SR & LR relationship between Ms & P by cointegration test and VECM.
– Examine the Granger causality between Ms & P.
– Explore the relationship between Ms & P with the technique of VAR, IRF and Variance
Decomposition.
– Examine the robustness of

Modeling Of Forecasting Inflation On Nepal Essay
CHAPTER FOUR
MODELING OF FORECASTING INFLATION IN NEPAL
4.1Introduction
Inflation is a burning economic problem in the developing countries like Nepal that brings adverse
effects like loss of purchasing power of national currency, leading to the aggravation of social
conditions and living standards. This also leads to uncertainty making domestic and foreign
investors reluctant to invest in the economy. Additionally, inflation broadens the country's terms of
trade causing domestic goods and services more expensive in the market. That is why; the monetary
authority of every economy should have the objective of maintaining stable price.
Inflation forecasting plays a central role in monetary policy formulation. Recent international
empirical evidence suggests that with the decline in inflation of recent years, a fairly widespread
phenomenon, the combined dynamics of this variable and its potential predictors, such as money or
different measures of the output gap, has changed, and inflation has become more unpredictable.
Univariate models tend to show a better forecasting capacity than those based on various inflation
theories, such as the Phillips curve. Traditionally, in industrialized countries the Phillips curve has
played a predominant role in inflation forecasting, and according to Stock and Watson (1999),
Atkenson and Ohanian (2001) and Canova, (2002), it would seem to perform better in terms of
forecasting error than other alternative models. In recent years there have

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