scholarly journals Relationship between lending interest rate, inflation rate and capital formation in Kenya

2021 ◽  
Vol 1 (5) ◽  
pp. 339-347
Author(s):  
Titus Mosoti Ogero
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Interest Rates ◽  
Inflation Rate ◽  
Time Series Data ◽  
Capital Formation ◽  
Series Data ◽  
Expectation Theory ◽  
Level Of Significance ◽  
The Relationship

The study seeks to understand the relationship between lending interest rate, inflation rate and capital formation in Kenya. Time series from World Bank for the 1988 to 2018 is employed. Development of literature is guided by expectation theory, classical theory of interest rate and the institutionalist theory of capital formation. The study finds capital formation, lending interest rate ad inflation rate time series data to be stationary at the 5% level of significance. This leads to the checking of the lag order used and estimating of VAR model. The results indicate that, current year’s; capital formation, inflation rate and lending interest rate are insignificant in determining next year’s level of capital formation. First lag of inflation rate is found positively significant in influencing lending interest rates as well as the first lag of lending interest rate is found significant on influencing itself. Capital formation first lag is found to be negatively significant in determining inflation rate. Lastly, inflation rate first lag is found to be positive

scholarly journals A Study on Estimation and Prediction of Vector Time Series Model Using Financial Big Data (Interest Rates)

2021 ◽  
Vol 12 (5) ◽  
pp. 309-316
Author(s):  
Jae-Hyun Kim, Chang-Ho An
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Prediction Model ◽  
Interest Rates ◽  
Time Series Data ◽  
Information Criteria ◽  
Series Data ◽  
Call Rate ◽  
Causality Test ◽  
Vector Autoregressive

Due to the global economic downturn, the Korean economy continues to slump. Hereupon the Bank of Korea implemented a monetary policy of cutting the base rate to actively respond to the economic slowdown and low prices. Economists have been trying to predict and analyze interest rate hikes and cuts. Therefore, in this study, a prediction model was estimated and evaluated using vector autoregressive model with time series data of long- and short-term interest rates. The data used for this purpose were call rate (1 day), loan interest rate, and Treasury rate (3 years) between January 2002 and December 2019, which were extracted monthly from the Bank of Korea database and used as variables, and a vector autoregressive (VAR) model was used as a research model. The stationarity test of variables was confirmed by the ADF-unit root test. Bidirectional linear dependency relationship between variables was confirmed by the Granger causality test. For the model identification, AICC, SBC, and HQC statistics, which were the minimum information criteria, were used. The significance of the parameters was confirmed through t-tests, and the fitness of the estimated prediction model was confirmed by the significance test of the cross-correlation matrix and the multivariate Portmanteau test. As a result of predicting call rate, loan interest rate, and Treasury rate using the prediction model presented in this study, it is predicted that interest rates will continue to drop.

scholarly journals Keterkaitan Instrumen Kebijakan Moneter dengan Tingkat Pengangguran

2018 ◽  
Vol 7 (4) ◽  
pp. 421-431
Author(s):  
Fitrawaty Fitrawaty
Keyword(s):  
Time Series ◽  
Interest Rates ◽  
Time Series Data ◽  
Policy Instruments ◽  
Series Data ◽  
Open Market ◽  
Vector Auto Regression ◽  
The Relationship ◽  
Auto Regression ◽  
Structural Vector

Penelitian ini bertujuan untuk menganalisis bagaimana interdependensi instrument kebijakan moneter dengan pengangguran di Indonesia selama periode tahun 2000 – 2011. Data yang digunakan adalah data time series yang diperoleh dari Bank Indonesia, Biro Pusat Statistik dan institusi lainnya. Penelitian ini menggunakan metode Vector Auturegression (VAR) dilanjutkan dengan Struktural Vector Auturegression (SVAR). Berdasarkan hasil interpretasi VAR dan SVAR, secara khusus diperoleh bahwa keterkaitan  antara instrumen moneter dengan pengangguran (UNEMP) memiliki arah yang berbeda. Variabel operasi pasar terbuka (OPT),  tingkat suku bunga diskonto (rDiskonto), dan tingkat bunga domestik (rDom), mempunyai arah yang negatif terhadap variabel pengangguran, sedangkan variabel giro wajib minimum (GWM), nilai tukar (EXC) mempunyai arah yang positif. Keseluruahan instrumen moneter secara parsial berpengaruh tidak signifikan terhadap UNEMP. Begitu juga setelah dilakukan shock dengan menaikkan OPT sebesar 5% pada tahun 2010, diperoleh bahwa variabel OPT, GWM, rDiskonto, rDOM, EXC, juga tidak berpengaruh signifikan terhadap pengangguran. This study is intended to analyze the correlation of monetary policy instruments with unemployment in Indonesia during the period 2000 - 2011. The data used are time series data obtained from Bank of Indonesia, the Central Statistics Bureau and other institutions. This study uses Vector Auto regression (VAR) method followed by Structural Vector Auto regression (SVAR). Based on the results of the interpretation of VAR and SVAR, it was found that the relationship between monetary instruments with unemployment (UNEMP) had different directions. Open market operations variable (OMO), discounted interest rates variable(discount), and domestic interest rates variable (FDOM), have a negative correlation to the unemployment variable, while the statutory reserve requirement (GWM), exchange rate (EXC) variables have a positive correlation. The partiality of monetary instruments has no significant effect on UNEMP. Likewise, after the shock of increasing OPT by 5% in 2010, it was found that the OMO variable, GWM, discount, FDOM, and EXC, also had no significant effects on unemployment.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI INFLASI DI INDONESIA

2016 ◽  
Vol 5 (2) ◽  
pp. 137
Author(s):  
Chairannisa Arjunita
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Money Supply ◽  
Inflation Targeting ◽  
Time Series Data ◽  
Multiple Linear Regression Model ◽  
Series Data

This study aims to  analyze the effect of interest rate, money supply,exchange rate and inflation targeting framework policy on inflation in Indonesia.The type of this research are descriptive and associative using time series data fromthe first quarter of 1997 until the fourth quarter of 2015 with documentation datacollected technique. Data were analyzed with multiple linear regression model, theprerequisite test (multicolinearity, autocorrelation and heteroscedasticity), t test, andF test. The result shows that (1) Interest Rates has positive and significant effect oninflation in Indonesia. (2) Money Supply has positive and not significant effect oninflation in Indonesia. (3) Exchange rate has negative and not significant effect oninflation in Indonesia.  (4) Inflation Targeting Framewrok Policy has positive andsignificant effect on inflation in Indonesia.

Analisis Kekakuan dan Faktor-faktor yang Memengaruhi Tingkat Suku Bunga Perbankan di Indonesia

2013 ◽  
Vol 8 (2) ◽  
pp. 26
Author(s):  
Eko Listiyanto ◽  
Telisa Aulia Falianty
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Interest Rates ◽  
Error Correction ◽  
Time Series Data ◽  
Error Correction Model ◽  
Least Square ◽  
Capital Adequacy ◽  
Series Data ◽  
Correction Model

<p align="center"><em>ABSTRACT</em></p><p><em>The research discusses the rigidity of interest rates on deposits and loans to changes in interest rate policies in the three groups of banks in Indonesia, and the factors that influence the interest rates on deposits and loans in the banking system. Rigidity of bank interest rates were analyzed with error correction model approach (Error Correction Model / ECM) using panel data. While the factors that influence the development of the banking interest rates were analyzed with multiple linear regression approach method of Generalized Least Square (GLS) using time series data. The period of data used from July 2005-March 2010.</em></p><p><em>Error Correction Model shows the slackness of interest rates response on deposits and loans toward the policy of interest rate. The rigidity of interest rates on deposits and loans in Indonesia is relatively slow when compared to some other countries.</em></p><p><em>Regression results with GLS method proves that the banking efficiency factor, bad credit and market share significantly influence the interest rates on deposits. While the borrowing rate is influenced by the rate of inflation, capital adequacy ratio, as well as bad credit. The results of this study suggest the importance of watching bad credit factors in making monetary policy because it can affect the interest rates on deposits and lending interest rates.  </em></p><p>ABSTRAK</p><p>Penelitian ini membahas kekakuan suku bunga deposito dan pinjaman untuk perubahan kebijakan suku bunga dalam tiga kelompok bank di Indonesia, dan faktor-faktor yang mempengaruhi suku bunga deposito dan pinjaman dalam sistem perbankan. Kekakuan suku bunga perbankan dianalisis dengan pendekatan error correction model (Error Correction Model / ECM) menggunakan data panel. Sedangkan faktor-faktor yang mempengaruhi perkembangan suku bunga perbankan dianalisis dengan metode pendekatan regresi linier berganda dari Generalized Least Square (GLS) dengan menggunakan data time series. Periode data yang digunakan dari Juli 2005-Maret 2010.</p><p>Error Correction Model menunjukkan kelambanan dari suku bunga respon deposito dan pinjaman terhadap kebijakan tingkat suku bunga. Kekakuan suku bunga deposito dan pinjaman di Indonesia relatif lambat jika dibandingkan dengan beberapa negara lain.</p><p>Hasil regresi dengan metode GLS membuktikan bahwa faktor efisiensi perbankan, kredit macet dan pangsa pasar secara signifikan mempengaruhi suku bunga deposito. Sementara tingkat pinjaman dipengaruhi oleh tingkat inflasi, rasio kecukupan modal, serta kredit macet. Hasil penelitian ini menunjukkan pentingnya menonton faktor kredit macet dalam membuat kebijakan moneter karena dapat mempengaruhi suku bunga deposito dan suku bunga kredit.</p>

scholarly journals PENGARUH SUKU BUNGA, PRODUK DOMESTIK BRUTO DAN NILAI TUKAR TERHADAP EKSPOR DI INDONESIA

2019 ◽  
Vol 4 (2) ◽  
pp. 300-317
Author(s):  
Okta Rabiana Risma ◽  
T. Zulham ◽  
Taufiq C. Dawood
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Gross Domestic Product ◽  
Interest Rates ◽  
Time Series Data ◽  
Domestic Product ◽  
Series Data ◽  
Auto Regressive ◽  
The Difference

This research aims to analyze the level of exports in Indonesia by using Time Series data from the year 1990 to 2015 against a variable interest rate loands, gross domestic product, and the exchange rate. Methods of analysis used i.e, Auto Regressive Distributed Lagged (ARDL). The results showed that the three variables have no Granger which is caused by the difference of the order on the test stasioner. Based on a test of wald for the short term that gained and the long-term gross domestic product, exchange rates and interest rates significantly influential credit toward export.Keywords:ARDL, export, interest rate loands, gross domestic product, exchange rates.AbstrakPenelitian ini bertujuan untuk menganalisis tingkat ekspor di Indonesia dengan menggunakan data Time Series dari tahun 1990 sampai 2015 terhadap variabel suku bunga kredit, produk domestik bruto, dan nilai tukar. Metode analisis yang digunakan yaitu AutoRegressive Distributed Lagged (ARDL).Hasil penelitian menunjukkan bahwa ketiga variabel tidak memiliki kointegrasi yang disebabkan oleh perbedaan ordo pada uji stasionernya. Berdasarkan uji wald didapat bahwa untuk jangka pendek dan jangka panjang produk domestik bruto, nilai tukar dan suku bunga kredit berpengaruh secara signifikan terhadap ekspor.

scholarly journals PENGARUH PDRB, INFLASI DAN SUKU BUNGA TERHADAP TINGKAT TABUNGAN MASYARAKAT PADA BANK SULUTGO

2019 ◽  
Vol 19 (5) ◽  
Author(s):  
NADYA LANI LENGKONG ◽  
VEKIE A. RUMATE ◽  
DAISY S.M. ENGKA
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Interest Rates ◽  
Time Series Data ◽  
Series Data ◽  
The Public ◽  
Goods And Services ◽  
North Sulawesi ◽  
Savings Rate ◽  
Increasing Demand

ABSTRAK Suatu daerah dapat dikatakan bertumbuh dan berkembang apabila adanya perkembangan perekonomian yang mana ditunjukkan dengan semakin meningkatnya permintaan akan barang dan jasa. Perubahan Permintaan yang tinggi dari masyarakat akan dapat meningkatnya jumlah uang beredar dan akan meyebabkan inflasi. Inflasi memiliki peran terhadap jumlah dana yang disimpan masyarakat di bank. Disamping tingkat suku bunga yang ditawarkan, inflasi juga memegang peran penting dalam mempengaruhi perilaku masyarakat untuk menabung. Inflasi merupakan kenaikan harga barang dan jasa secara menyeluruh. Inflasi yang tinggi akan mengurangi nilai riil dari uang yang disimpan, dengan kata lain Inflasi adalah peristiwa yang cenderung mendorong naiknya tingkat harga. Selain PDRB dan inflasi, faktor yang turut mempengaruhi pertumbuhan perbankan melalui peningkatan jumlah tabungan masyarakat adalah tingkat suku bunga simpanan.Tujuan dari penelitian ini untuk menganalisis apakah PDRB, laju inflasi, dan tingkat suku bunga berpengaruh positif dan signifikan terhadap tingkat tabungan masyarakat pada tahun 2006 - 2015. Teknik analisis yang digunakan adalah data sekunder kurun waktu (time series).Dan hasil penelitian menunjukan bahwa PDRB mempunyai pengaruh terhadap tingkat tabungan masyarakat Sulawesi Utara, sedangkan Inflasi dan Suku Bunga secara bersama-sama tidak berpengaruh terhadap tingkat tabungan masyarakat di Sulawesi Utara. Kata Kunci; PDRB, Inflasi dan Suku Bunga ABSTRACT                     An area can be said to grow and expand if there is an economic development which is indicated by the increasing demand for goods and services. Changes The high demand from the public will be able to increase the money supply and will lead to inflation. Inflation has a role to the amount of funds deposited by the public at the bank. In addition to the interest rates offered, inflation also plays an important role in influencing the behavior of people to save. Inflation is an increase in the price of goods and services as a whole. High inflation will reduce the real value of the money saved, in other words Inflation is an event that tends to push up the price level. In addition to GRDP and inflation, factors that influence growth banking through an increase in the amount of public savings is the deposit interest rate.                    The purpose of this research is to analyze whether PDRB, inflation rate, and interest rate have positive and significant influence to community saving level in 2006-2015. The analysis technique used is time series data.                    And the results of the study show that GRDP has an influence on the savings rate of the people of North Sulawesi, while Inflation and Interest Rates together do not affect the level of community savings in North Sulawesi. Key Word : PDRB, Inflation, Interest Rates

scholarly journals Pengaruh Pendapatan , Jumlah Nasabah Dan Tingkat Suku Bunga Terhadap Penyaluran Kredit Pt Pegadaian Cabang Kabupaten Jember Periode 2013 -2017

2019 ◽  
Vol 15 (1) ◽  
pp. 151-174
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Interest Rate ◽  
Interest Rates ◽  
Time Series Data ◽  
Computer Software ◽  
Secondary Data ◽  
Series Data ◽  
The Interest Rate ◽  
Number Of Customers

The research objective was to analyze the large number, number of customers, and interest rates on the loan distribution of PT Pegadaian Branch of Jember Regency.The type of data used in this study is secondary data consisting of time series data on income, number of customers obtained through the pawnshop office which is the object of research and interest rates for the period 2013-2017 obtained from BI which is the object of the research. The data is processed using computer software "SPSS 22" with multiple regression analysis methods. The Pawnshop Branch of Kabupaten Jember is very positive and significant towards lending to PT Pegadaian Branch of Kabupaten Jember, while the Interest Rate does not significantly influence the lending of PT Pegadaian Branch of Kabupaten Jember. Together, it focuses positively and significantly on the loan distribution of PT Pegadaian Branch of Jember Regency

CAUSAL RELATIONSHIP OF ENERGY CONSUMPTION AND ECONOMIC GROWTH – A CASE STUDY OF PAKISTAN

2021 ◽  
Vol 9 (1) ◽  
pp. 139-164
Author(s):  
Saddam Hussain ◽  
Chunjiao Yu
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Energy Consumption ◽  
Causal Relationship ◽  
Inflation Rate ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Series Data ◽  
Relationship Of

This paper explores the causal relationship between energy consumption and economic growth in Pakistan, applying techniques of co-integration and Hsiao’s version of Granger causality, using time series data over the period 1965-2019. Time series data of macroeconomic determi-nants – i.e. energy growth, Foreign Direct Investment (FDI) growth and population growth shows a positive correlation with economic growth while there is no correlation founded be-tween economic growth and inflation rate or Consumer Price Index (CPI). The general conclu-sion of empirical results is that economic growth causes energy consumption.

scholarly journals PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA CURAH HUJAN EMPAT KABUPATEN DI PROVINSI JAWA TENGAH

2019 ◽  
Vol 8 (4) ◽  
pp. 418-427
Author(s):  
Eko Siswanto ◽  
Hasbi Yasin ◽  
Sudarno Sudarno
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Space Time ◽  
Series Data ◽  
Inverse Distance Weighted ◽  
Modeling And Forecasting ◽  
Distance Weighted ◽  
The Relationship ◽  
Inverse Distance

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model to modeling volume of rainfall four locations in Jepara Regency, Kudus Regency, Pati Regency, and Grobogan Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR (11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on rainfall Pati Regency influenced by the rainfall in other regencies. Keywords: GSTAR, RMSE, Rainfall

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