Lagrange Multiplier Test Research Articles

CONVERGENCE OF WHOLESALE ELECTRICITY PRICES ACROSS EUROPEAN MARKETS: ARE WE THERE YET?

European electricity market integration has been a research focus, especially after the third electricity directive emphasizing the internal market. Electricity markets are characterized by immediate consumption with storage and transmission constraints, leading to unique price dynamics. Price convergence in European markets can lead to competitive pricing, advocating market integration. This research examines whether European wholesale spot electricity prices converge. Prior literature uses sigma and beta-convergence to test price convergence. We have examined the stochastic convergence of prices across 19 European nations from 2013 to 2021 utilizing monthly data. For this analysis, we employed LM tests incorporating trend breaks grounded on the RALS regression framework. RALS-LM tests are more powerful than linear tests when structural breaks and nonnormal errors are present. LM and RALS-LM unit root tests with two trend breaks resulted in rejection of the unit root hypothesis for all countries, suggesting relative wholesale prices are stationary. Thus, shocks to relative prices are transient, supporting price convergence at the wholesale level. This result should be considered carefully as it contradicts the results from recent literature that examines retail electricity prices using beta- sigma- and club convergence. The policy implications of this finding can provide a foundation for establishing policies that promote a harmonized and integrated European electricity market.

Foreign Direct Investment and Financial Development: Evidence from Selected Arab League Countries

This study examined the impact of foreign direct investment on financial development in selected Arab League countries (Algeria, Comoros, Egypt, Jordan, Kuwait, Lebanon, Mauritania, Oman, and Qatar) for the period from 2010 to 2021. The study used one explanatory variable — financial development — and one explained variable — foreign direct investment. To obtain reliable and valid results, panel data were analyzed, and various tests were carried out, including the Chow test, Breusch-Pagan Lagrange multiplier test, Hausman test, Jarque-Bera normality test, Wooldridge test, generalized least squares, and ordinary least squares. The robust model of the study revealed a positive and significant relationship between foreign direct investment and the financial development index, human development index, and interest rate. Also, there is a negative and significant relationship between foreign direct investment and the consumer price index and domestic credit to private sector. Based on these findings, the study recommends that Arab League countries’ policies and strategies should attract foreign investors to maintain and sustain economic developmental goals for healthy, literate, and wealthy lives.

The Impacts of Globalization, Economic Growth, Population and Urbanization on Carbon Dioxide Emissions in Afghanistan

The atmospheric carbon dioxide emissions have increased since last few years in Afghanistan. This increasing trend in carbon emissions may cause global warming, climate change and environmental pollution. Consequently, these indicated threats may suffer human life and ecological conditions in near future. Therefore, this study examines the impacts of globalization, economic growth, population and urbanization on carbon emissions in Afghanistan using annual time series data for the period 1990 – 2020. The study used the Augmented Dickey Fuller and Phillips–Perron unit root tests, the Breusch – Godfrey serial correlation Lagrange multiplier (LM) test and the autoregressive distributed lag (ARDL) bounds test to examine the short and long-run relationship of globalization, economic growth, population and urbanization with carbon emissions. The empirical results show that globalization, economic growth and population have a significant positive short and long-run relationship with carbon emissions. While urbanization has a significant short-run negative and long-run positive relationship with carbon emissions. Based on results, it is highly recommended that government should design environment friendly policies related to globalization, economic growth, population and urbanization to reduce environmental pollution in Afghanistan.

The Influence of Financial Ratios and Firm Size on Stock Return

Researchers analyze financial ratio data using a quantitative approach to determine the effect on the company's stock return. Researchers formulated four research hypotheses. The data will be modeled using the Panel Data Regression method with the help of E-Views 12 Student software. With purposive sampling techniques, researchers will use stock closing price data and financial statements from 9 Properties and Real Estate companies listed on the Indonesia Stock Exchange (period 2018 to 2022). With the chow test and lagrange multiplier test, researchers will model the data using a common effect model. The results showed that the ROA of der, CR, and FS, either simultaneously or partially, did not have a significant effect on stock returns. Based on signal theory, capital owners will receive bad signals from the company because the variables ROA, DER, CR, FS are considered unable to influence the company's stock return.

Savings Mobilization Efforts of the Nigerian Money Market and Economic Growth

Economic growth is a function of some productive efforts among which savings mobilizations is considered very vital. This study examined saving mobilization efforts of the Nigerian money market and the effects on economic growth during the year 2001 – 2022.Vested with the objectives to investigate the effect of banking density, savings rates and money supply on economic growth. The study relied on time series data sourced from the publication of the Central Bank of Nigeria. Gross Domestic Product Growth Rate (GDPGR) was adopted as dependent variable, while Banking Density (BD), Savings Rates (SR) and Money Supply (MS) were the independent variables. Augmented Dickey Fuller (ADF) unit root test was employed, to test the stationarity. The Auto Regressive Distributive Lag (ADRL) was used to ascertain the relationship between the variables alongside Vector Error Correction Model (VCM). Post estimation diagnostic tools used include; Breuch-Godfrey serial correlation LM test and the CUSUM test for stability. From the ARDL, β-coefficient and the associated probabilities were adopted to determine the extent and direction of relationship on economic growth. Data were tested at 5% level of significance, it was discovered that banking density and savings rates affected economic growth positively but with insignificant effects, while money supply affected economic growth negatively with insignificant effect. The study therefore recommends amongst other, that stakeholders, be directed towards entrenching higher banking density as opposed to banking desert, and that money supply should be made dynamic in accordance with economic realities.

PENGARUH TINGKAT PARTISIPASI ANGKATAN KERJA, KUALITAS PENDUDUK, DAN TINGKAT PENGANGGURAN TERBUKA TERHADAP PERTUMBUHAN EKONOMI DI PROVINSI SUMATERA UTARA

This study aims to analyze the influence of the Labor Force Participation Rate, population quality, and the level of open response to economic growth in North Sumatra Province. This research uses secondary data from 2017-2021. The model used is the panel data regression model with three types of estimation, namely the commond effect model, the fixed effect model and the random effect model. To determine which model is best for use in the test through three tests Chow test, Hausmant test and LM test. Based on the test results that have been carried out, the selected model is the fixed effect model. The partial results show that the Variable Labor Force Participation Rate has a positive and significant effect on economic growth in North Sumatra, while the quality of the population and the level of open response have a negative and significant effect on economic growth in North Sumatra and together (simultaneously) the labor force participation rate. population quality, and the level of open damping have a positive effect on economic growth in North Sumatra Province. As well as the test results for the coefficient of determination obtained by the R Square value showing a value of 0.351 or 35.1% indicating that the ability of the independent variable to explain the effect on the dependent variable and the remaining 64.9% can be explained by other variables outside the research variables. Recommendations for the election of the government of North Sumatra can provide training to job seekers so that they have skills, and the government has achievements in opening jobs so that it will reduce action and can increase economic growth.

Analysis of Poverty and Unemployment on Human Development Index in West Kalimantan in 2020-2022

The Human Development Index (HDI) is built through a three-dimensional approach, namely knowledge, decent living standards, and longevity and healthy living. In the longevity and healthy life dimension, life expectancy at birth is the benchmark, and the expected years of schooling and average years of schooling are indicators used in the knowledge dimension. Meanwhile, a decent standard of living as measured by annual capita expenditure is an indicator in the HDI. West Kalimantan's HDI in 2020 to 2021 experienced a fairly low increase, then in 2021 to 2022, West Kalimantan's HDI experienced a very significant increase and even occupied the first position of the highest HDI increase in Kalimantan Island. The increase in West Kalimantan's HDI every year is influenced by a number of variables that affect HDI. The objective of this research is to examine the influence of poverty and unemployment on the Human Development Index (HDI) by analyzing the outcomes derived from the most effective panel data regression model. This study involves several phases, including data input, conducting multicollinearity tests, analyzing using panel data regression models, finding the best model with the Chow test, Hausman test, and Lagrange Multiplier test, as well as classical assumption tests, and output interpretation. The factors considered in this research comprise HDI (Y), poverty (X1), and unemployment (X2) in West Kalimantan. The examination indicates that the Fixed Effect Model (FEM) stands out as the most effective model, demonstrating an adjusted R-squared value of 99.14% where the variables of poverty (X1) and unemployment (X2) have a significant influence on HDI (Y).

PENGARUH BELANJA TRANSFER KE DAERAH DAN DANA DESA (TKDD) TERHADAP KETIMPANGAN PEMBANGUNAN DI INDONESIA

This research was conducted on the topic of the Influence of Regional Transfer and Village Fund Expenditure as government spending instruments in the state budget on Development Inequality in Indonesia. The study utilized Regional Transfer and Village Fund Expenditure (TKDD) data as the independent variable. Meanwhile, the dependent variables were the Regional Disparity Index (Williamson Index) and the Gini Ratio as representations of regional inequality in Indonesia. The data used consisted of panel data, including TKDD expenditure, per capita GRDP, and the population of each province in Indonesia from 2017 to 2021. The research employed a quantitative method using panel data regression analysis (Pooled data). Based on the LM Test results, the Random Effect Model was found to be better than the Common Effect Model for estimating the regression model between TKDD and the Williamson Index (IW) variables. Meanwhile, the best model for estimating the regression model between TKDD and the Gini Index (IG) variables was the Fixed Effect Model after conducting the Chow Test and Hausman Test. Regression testing results indicated that the TKDD variable had a negative and non-significant relationship with the IW variable (development inequality). This is evident from the coefficient value of -0.101798 and a probability value of 0.6012 (greater than 0.05), meaning it is not significant. Similarly, the regression results between the TKDD variable and the IG variable showed a coefficient value of -16477.71 and a probability value of 0.1410 (greater than 0.05), indicating non-significance.

Spatial patterns and sociodemographic predictors of chronic obstructive pulmonary disease in Florida.

Chronic obstructive pulmonary disease (COPD) is a chronic, inflammatory respiratory disease that obstructs airflow and decreases lung function and is a leading cause death globally. In the United States (US), the prevalence among adults is 6.2%, but increases with age to 12.8% among those 65 years or older. Florida has one of the largest populations of older adults in the US, accounting for 4.5 million adults 65 years or older. This makes Florida an ideal geographic location for investigating COPD as disease prevalence increases with age. Understanding the geographic disparities in COPD and potential associations between its disparities and environmental factors as well as population characteristics is useful in guiding intervention strategies. Thus, the objectives of this study are to investigate county-level geographic disparities of COPD prevalence in Florida and identify county-level socio-demographic predictors of COPD prevalence. This ecological study was performed in Florida using data obtained from the US Census Bureau, Florida Health CHARTS, and County Health Rankings and Roadmaps. County-level COPD prevalence for 2019 was age-standardized using the direct method and 2020 US population as the standard population. High-prevalence spatial clusters of COPD were identified using Tango's flexible spatial scan statistics. Predictors of county-level COPD prevalence were investigated using multivariable ordinary least squares model built using backwards elimination approach. Multicollinearity of regression coefficients was assessed using variance inflation factor. Shapiro-Wilks, Breusch Pagan, and robust Lagrange Multiplier tests were used to assess for normality, homoskedasticity, and spatial autocorrelation of model residuals, respectively. County-level age-adjusted COPD prevalence ranged from 4.7% (Miami-Dade) to 16.9% (Baker and Bradford) with a median prevalence of 9.6%. A total of 6 high-prevalence clusters with prevalence ratios >1.2 were identified. The primary cluster, which was also the largest geographic cluster that included 13 counties, stretched from Nassau County in north-central Florida to Charlotte County in south-central Florida. However, cluster 2 had the highest prevalence ratio (1.68) and included 10 counties in north-central Florida. Together, the primary cluster and cluster 2 covered most of the counties in north-central Florida. Significant predictors of county-level COPD prevalence were county-level percentage of residents with asthma and the percentage of current smokers. There is evidence of spatial clusters of COPD prevalence in Florida. These patterns are explained, in part, by differences in distribution of some health behaviors (smoking) and co-morbidities (asthma). This information is important for guiding intervention efforts to address the condition, reduce health disparities, and improve population health.

Government Expenditure and Economic Growth: A Cross-Country Analysis

This paper empirically analyses the relationship between Economic Growth measured in terms of GDP Growth and Government Expenditure, GDP and Population. It employs annual cross-section time series data of the concerned variable of 117 countries from 2001 to 2021. Random Effect model was used for the analysis. The pool-ability of data is tested by the Breusch and Pagan LM test which confirmed that Pooled OLS is not appropriate for the model. The Hausman Specification Test was then conducted for choosing between the Fixed Effect or Random Effect model. The Hausman Specification Test for the Model suggests the Random effect model is appropriate for the analysis of the data. Thus, Random effect regression is used to find the consequences of explanatory and the control variables on the dependent variable. Government Expenditure as an explanatory variable has a positive relationship with the Economic Growth, even in the case of controlling for Population and the Trade Openness. Both the control variable is depicted to have positive relationship with the Economic Growth.

Internal Variables and Macroeconomic Factors as Determinants of Profitability in Islamic Banking Indonesia

The purpose of this research was to analyse the influence of internal and macroeconomic variables on the profitability of the Islamic banking industry in Indonesia. A panel data regression approach, applying fixed effect and common effect models in order to to address potential biases in the estimation was used. The research sample consisted of five Islamic banks and covered the period from Q1 to Q4 of 2022. Chow test and Lagrange multiplier test were used to compare the analysis results. The used control variables included financing quality, financing to deposit ratio, exchange rate, and gross domestic product growth. The research was also based on economic, efficiency, and productivity theories in Islamic banking. Findings, The research results showed that the Islamic banking industry in Indonesia was increasingly compliant with prevailing regulations. The Bank Indonesia's policy interest rate (BI rate) did not significantly influence the profitability. Inflation had a negative impact on profitability, while the capital adequacy ratio showed a non-linear effect. All tested control variables exhibited an influence on profitability. Financing quality and exchange rate had negative impacts, while liquidity and economic growth had positive impacts on the profitability of the Islamic banking industry in Indonesia. The novelty of the paper is visible in the panel data regression approach that uses fixed effect and common effect models and provides an effective way to address estimation bias. Additionally, this research identified control variables that have a significant impact on profitability, including financing quality, liquidity, exchange rate, economic growth, and capital adequacy ratio to present breakthroughs and innovations.

An In-Depth Analysis of Credit, Capital, and Operational Risks on Regional Development Banks' Performance Amidst the Covid-19 Pandemic

The Covid-19 pandemic has hit the world since the end of 2019 and has damaged the world economy, including Indonesia. Banking as a financial institution that provides funding to companies is also affected. Because the pandemic has reduced the company's performance, and this decline in performance has had an impact on banking. The aim of this research is to test whether the Covid-19 pandemic has an impact on the relationship between risk factors and bank performance. Bank performance is measured by profitability which consists of return on assets (ROA) and return on equity (ROE), while bank risk in this study consists of credit risk, liquidity risk, capital, operational risk and the Covid-19 pandemic. The population in this research is the Regional Development Banks (BPD) in Indonesia totaling 34 banks with a sample of 30 banks. The observation period was 4 years with quarterly data so that 320 observation data were collected. Hypothesis testing uses panel data regression, and to select the best regression model, the model will be tested using the Chow-test, Hausman-test, and Lagrange Multiplier test. After the model test was carried out, the fixed effect model was selected as the best model. The research results show that credit risk and operational risk have a significant and negative influence on all profitability, both ROA and ROE. Meanwhile, liquidity risk (LDR) has no effect on both types of profitability, while capital has an effect on ROE but has no effect on ROA. Another interesting result is that the Covid-19 pandemic has no impact on the influence of risk on bank performance.

Analisis Tingkat Pengangguran Terbuka, Human Capital Dan Jumlah Penduduk Terhadap Kemiskinan di Sumatera Utara

<p>This research aims to find out how much influence the unemployment rate, human capital and population have on poverty in the 2018-2022 period. This research uses quantitative methods with descriptive analysis. The data used in this research is secondary data sourced from the Central Statistics Agency (BPS) of North Sumatra for 4 years from 2018-2022. The data analysis technique uses Random Effect based on the results of the Lagrange Multiplier test. The results of this research show that (1) the independent variables, namely open unemployment, human capital, and population have a significant effect on poverty in North Sumatra province, (2) the level of open unemployment and population have a positive effect and have a significant influence on poverty in North Sumatra, and (3) the Human Capital variable has a negative effect and has a significant influence on poverty in North Sumatra.</p>

DETERMINANT OF CAPITAL ADEQUACY RATIO USING INTERVENING VARIABLE RETURN ON ASSETS

This research is intended to analyze the influence of inflation variables, Loan to Deposit Ratio (LDR) on the Return On Assets (ROA) profitability ratio and on the Capital Adequacy Ratio (CAR). This is based on the phenomenon of inconsistencies in various studies from what is happening in reality, thus encouraging researchers to carry out research again. This research is a type of quantitative descriptive research with multiple regression analysis method for panel data using 9 cross section samples and 6 years as a time series. This research formula is to maximize the value of the CAR through ROA as an intervening variable using the research object of banking sector companies on the Indonesia Stock Exchange. Two research models were developed and integrated into one research model, each of which went through the model selection test stages, Chow Test, Hausman Test, and Lagrange Multiplier Test. The results of the first research model; that inflation can explain the impact on ROA with a negative correlation where these results confirm the applicable theory. Another result in the second research model is that the LDR can significantly explain its influence on the CAR with a negative correlation and this result is also in accordance with the applicable theory. The other variables cannot explain their influence on the endogenous variable ROA in the first model and the CAR in the second model. It is hoped that these results can help as a guide for banking practitioners in Indonesia to be able to maximize the CAR.

Do ESG ratings and COVID-19 severity score predict stock behavior and market perception? Evidence from emerging markets

PurposeThe purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.Design/methodology/approachThe authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.FindingsThe authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.Practical implicationsFavorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.Social implicationsThe findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.Originality/valueThe study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.

GARCH Models and Distributions Comparison for Nonlinear Time Series with Volatilities

The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is extensively used for handling volatilities. However, with numerous extensions to the standard GARCH model, selecting the most suitable model for forecasting price volatilities becomes challenging. This study aims to examine the performance of different GARCH models in forecasting crude oil price volatilities using West Texas Intermediate (WTI) data. The models considered are the standard GARCH, Integrated GARCH (IGARCH), Exponential GARCH (EGARCH), and Golsten, Jagannathan, and Runkle GARCH (GJR-GARCH), each with normal distribution, Student’s t-distribution, and Generalized Error Distribution (GED). To evaluate the performance of each model, the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) are used as the model selection criteria, along with forecast accuracy measures such as absolute error, root mean squared error (RMSE), and mean absolute error (MAE). Post-estimation tests, including the Autoregressive Conditional Heteroskedasticity Lagrange Multiplier (ARCH-LM) test and the Ljung-Box test, are conducted to ensure the adequacy of all models. The results reveal that all GARCH models are suitable for modeling the data, as indicated by statistically significant estimated parameters and satisfactory post-estimation outcomes. However, the EGARCH (1, 1) model, particularly with Student’s t-distribution, outperforms other models in both data fitting and accurate forecasting of nonlinear time series.

CORPORATE DYNAMICS: Exploring the Nexus of Company Size, Leverage, Profitability, and the Regulatory Role of Variable Tax Aggressiveness

Tax avoidance is one of the efforts to minimize the tax burden that is often carried out by companies, because it is still within the framework of applicable tax regulations. The purpose of this study is to empirically prove the effect of Company Size, Leverage, Profitability simultaneously on Company Value in mining sector companies listed on the IDX in 2017-2021, the total population in this study is 47 companies. Samples were obtained using the purposive sampling method, so 41 companies were obtained. The research approach used in this study is quantitative research. The secondary data used is obtained from financial statements according to the selected criteria. The data collection method is carried out using purposive sampling by processing data using the Eviews software tool version 9. Data analysis using Panel Data Regression and Moderating Regression Analysis. Based on the paired test model using Chow Test, Hausmant Test and Lagrange Multiplier Test, the best model used is the Fixed Effect Model. The calculation results state that Company Size, Leverage and Profitability together have a significant positive effect on the Company Value of Mining Companies listed on the Indonesia Stock Exchange during the 2017-2021 period.

A conditional linear combination test with many weak instruments

We consider a linear combination of jackknife Anderson-Rubin (AR), jackknife Lagrangian multiplier (LM), and orthogonalized jackknife LM tests for inference in IV regressions with many weak instruments and heteroskedasticity. Following I.Andrews (2016), we choose the weights in the linear combination based on a decision-theoretic rule that is adaptive to the identification strength. Under both weak and strong identifications, the proposed test controls asymptotic size and is admissible among certain class of tests. Under strong identification, our linear combination test has optimal power against local alternatives among the class of invariant or unbiased tests which are constructed based on jackknife AR and LM tests. Simulations and an empirical application to Angrist and Krueger’s (1991) dataset confirm the good power properties of our test.

Banks Amid Economic Recovery: Understanding Macroeconomic Influences, Firm Valuation, and the Investor Confidence Paradox

This study investigates the intriguing relationship between a robust macroeconomic environment during economic recovery and the signaling of increased firm value within the banking sector. It underscores the importance of macroeconomic factors in investors' evaluation of banking firms and examines the rationale behind investors not exhibiting strong reactions to favorable macroeconomic signals. Utilizing an explanatory research method, the study analyzes secondary data from financial reports of 42 companies listed on the Indonesia Stock Exchange during 2010-2020. A panel data regression approach is employed, incorporating common effect, fixed effect, and random effect models, validated through Chow, Hausman, and Lagrange Multiplier (LM) tests. Resulting insights explain the paradoxical absence of a robust investor response despite banks' resilience amid the economic turmoil. The theoretical implication is that a stable macroeconomic environment typically projects positive signals for the banking sector, enhancing investor confidence and potentially driving up share prices. The study reveals substantial practical implications concerning the macroeconomic influences on firm value signals in the banking industry during economic recovery. Banks are advised to recalibrate their strategies and operations to capitalize on or navigate the risks associated with recovery periods.

Revisiting the Neighborhood Effects on Disadvantaged Households in Indonesia

The latest statistics of 2022 record 9,57 percent of the Indonesian population living in poverty. As most of the study in this field merely focuses on the internal factors of poverty, this study contributes to providing more perspectives for poverty alleviation by revisiting spatial linkages on poor households’ income in East Java, the second most populated province in the economy. This study employs spatial econometrics analysis in a three-step procedure: (i) designing spatial weight matrix within nearest districts, (ii) doing Moran's I Test to identify spatial effects on the variables, lastly (iii) doing LM Test to find best regression model. Estimates on the SUSENAS 2017 database show that both Ordinary Least Square (OLS) and General Nesting Spatial (GNS) models provide similar results. Nonetheless, when compared with Akaike’s Information Criterion (AIC) model, the GNS model provides better accuracy. This means accommodating spatial effect is imperative. This study also finds a positive spillover of poor households’ income within neighboring districts. This implies the existence of multiplier effects in a household’s economic activities that later might form clusters of poverty. These suggest that the Sustainable Livelihood Approach interventions in the province should take into account differences in social institutions and other socio-cultural characteristics.