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The agricultural sector remains the backbone of several emerging economies, including Kenya, where it contributes 34% to its gross domestic product (GDP). However, access to financing for agricultural activities appears to be very low compared to developed economies. Following this, governments in a number of countries have sought to introduce banking sector regulations to facilitate increased funding to the agricultural sector. Taking motivation of the interest rate capping regulations by the Central Bank of Kenya (CBK) in 2016, this paper examined the effect of these interest rate ceiling regulations on agri-lending in Kenya.

The paper employs random effects technique to estimate a panel data of 26 commercial banks in Kenya from 2014 to 2018 using the ratio of loans to agricultural sector to gross loans and the natural logarithm of loans to agricultural sector as proxies for agri-lending. Bank size, equity, asset quality, liquidity, revenue concentration and bank concentration are employed as control variables.

The results of the panel regression estimations show that the introduction of the interest cap resulted in increases in the proportion and growth in agri-lending compared with the pre-interest cap period. In addition, large banks and highly capitalised banks were found to be associated with lower agri-lending, with differences in the effects across pre-cap and post-cap periods.

From a policy perspective, the findings highlight the effectiveness of interest rate capping in meeting this objective and supports the calls for strengthening cooperation between the government and key stakeholders in the financial sector. This will allow for the effective enforcement of policies by the regulatory powers in a manner that guarantees sound and dynamic financial systems, particularly within the agricultural sector.

As far as the authors are aware, this the first paper to examine the effect of the interest rate cap regulation on agri-lending in Kenya.

The authors take a historical perspective and compare office market performance metrics and CMBS loan delinquency rates over the past two years with previous downturns.

What will happen to the office sector in the post-pandemic era? we examine this question from three perspectives. First, the authors discuss the (short-term) risk of commercial real estate investment with high inflation and rising interest rates. If investors want to use CRE as an inflationary hedge, the cash flow must increase enough to counteract growing cap rates given rising interest rates.

As it turns out, the COVID-19 recession has been notably innocuous. Third, the authors focus on medical office space – an emerging investment option for the office sector.

The authors remain somewhat positive (or at least less downbeat) about the future of the office market based on the data they reviewed.

The office market is experiencing an odyssey rather than an exodus, at least in the short run. However, the authors remain cautious and they are monitoring key signs, prepared for the possibility of (r)evolutionary change in the office sector.

This paper examines the sluggish adjustment of deposit interest rate categories with response to policy rate changes in a developing economy.

Symmetric and asymmetric error correction models (ECMs) are employed to test the pass-through effect and adjustment speed of deposit rates when above or below their equilibrium levels.

The findings reveal an incomplete pass-through effect in both the short run and long run while mixed results of symmetric and asymmetric adjustment speed across the different deposit rate categories are observed. Collusive pricing arrangement behavior is supported by deposit rate categories that adjust more rigidly upwards than downwards, while negative customer reaction behavior is supported by deposit rate categories that adjust more rigidly downwards than upwards.

Even though the findings indicate an aspect of increased responsiveness over the period, the sluggish adjustment of deposit rates imply that monetary policy is still ineffective and not uniform across the different deposit rate categories.

To the best of the authors' knowledge, this is the first study to empirically examine both symmetric and asymmetric adjustment behavior of deposit interest rate categories in Kenya. The findings are key to policy makers as they provide insights on how long it takes to adjust different deposit rate categories to monetary policy decisions. In addition, the behavior of deposit rates partly explains why interest rates capping was imposed in Kenya in 2016.

Cryptocurrency arose, and grew in popularity, following the financial crisis of 2008 built upon a promise of decentralizing money and payments. An examination of the history of money and banking in the United States demonstrates that stable money benefits from strict controls and commitments by a centralized government through chartering restrictions and a broad safety net, rather than decentralization. In addition, financial crises happen when the government allows money creation to occur outside of official channels. The US central bank is then forced into a policy of supporting a range of money-like assets in order to maintain a grip on monetary policy and some semblance of financial stability.

In addition, this chapter argues that cryptocurrency as a form of shadow money shares many of the problematic attributes of both the privately issued bank notes that created instability during the “free banking” era and the “shadow banking” activities that contributed to the 2008 crisis. In this sense, rather than being a novel and disruptive idea, cryptocurrency replicates many of the systemically destabilizing aspects of privately issued money and money-like instruments.

This chapter proposes that, rather than allowing a new, digital “free banking” era to emerge, there are better alternatives. Specifically, it argues that the Federal Reserve (Fed) should use its tools to improve public payment systems, enact robust utility-like regulations for private digital currencies and limit the likelihood of bubbles using prudential measures.

The purpose of this paper is to study the effect of credit record overconfidence on the use of alternative financial services (AFSs).

Using data from the 2018 National Financial Capability Study (NFCS), the authors estimate logistic regressions on the use of at least one AFS by adding a credit record confidence variable that captures deviations between self-assessments of credit record management and the number of reported behaviors that would negatively affect aspects of a Fair Isaac Corporation (FICO) score.

The authors find that respondents with credit record overconfidence have over two times higher odds (123.9%) of using AFS than the odds of respondents with financial knowledge overconfidence (46.8%), relative to their reference categories. When compared directly, those with only credit record overconfidence have 32.6% higher odds of using AFS than those with only financial knowledge overconfidence.

The results provide implications for education programs, not only for vulnerable groups at higher risk for AFS use but also for those with cognitive biases, such as credit record overconfidence. Potential solutions include personal financial education that includes debiasing and behavioral techniques for overconfidence.

This paper studies, for the first time, the effect of deviations between actual and perceived credit record management on AFS use.

With refineries contributing 68% of CO₂ emissions from stationary combustion sources alone, smart technologies and the circular economy (CE) model for resource loop optimization can be a solution for carbon neutrality, especially within petroleum. Thus, this study aims to explore energy conservation by green technology improvement as a CE strategy for resource loop optimization and digital incorporation to maximize reprocessing lead ability rate and carbon-neutral benefits.

A game theory approach with Stackelberg equilibrium is considered under government cap-and-trade regulation to stimulate green technology improvement. The refinery acts as a Stackelberg leader and invests in green technology and the retailer as the Stackelberg follower, collects end-of-life lubricants against refund price and offers a two-part-tariff contract to the manufacturer having a significant role in smart technologies.

First, green technology improvement is directly influenced by the reprocessing capability and refund price and digital technologies are significant to consider. Second, a two-part-tariff contract coordinates the supply chain for limited reprocessing capability by the retailer. Lastly, the government can effectively manipulate the development of green technology by changing the permit price depending on the intentions.

The primary limitation is this study has focused on the petroleum sector and data was referenced from the oil refineries of a single country.

Overall, this study provides empirical guidance for policymakers on how to leverage energy-efficient smart technologies for lubricant reprocessing, enabling resource optimization as part of a CE strategy in the petroleum industry and advancing sustainable development goals.

The suggested model responds to the contemporary literature related to CO₂ emissions and CE initiatives across the petroleum sector with the extended role of smart technologies and government cap-and-trade regulations.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

This paper studies the dynamic effects of selected macroeconomic factors on the performance of the housing market in Kenya using Autoregressive Distributed Lag (ARDL) Models. This study aims to explain the dynamic effects of the macroeconomic factors on the three indicators of the housing market performance: housing prices growth, sales index and rent index.

This study used ARDL Models on time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited.

The results indicate that household income, gross domestic product (GDP), inflation rates and exchange rates have both short-run and long-run effects on housing prices while interest rates, diaspora remittance, construction output and urban population have no significant effects on housing prices both in the short and long run. However, only household income, interest rates, private capital inflows and exchange rates have a significant effect on housing sales both in the short and long run. Furthermore, household income, GDP, interest rates and exchange rates significantly affect housing rental growth in the short and long run. The findings are key for policymaking, especially at the appraisal stages of real estate investments by the developers.

The authors recommend the use of both the traditional hedonic models in conjunction with the dynamic models during real estate project appraisals as this would ensure that developers only invest in the right projects in the right economic situations.

The imbalance between housing demand and supply has prompted an investigation into the role of macroeconomic variables on the housing market in Kenya. Although the effects of the variables have been documented, there is a need to document the short-run and long-term effects of the factors to precisely understand the behavior of the housing market as a way of shielding developers from economic losses.

Given the coincidental and sustained rise in house prices and foreign capital flows in Kenya, this study aims to understand whether a long-run relationship exists between real diaspora remittances and real house prices.

This study uses data from 2004-Q1 to 2020-Q4 and applies an autoregressive distributed lag model for estimation.

The results indicate that a positive and significant relationship exists between real remittances and real house prices in Kenya in the long run.

To the best of the authors’ knowledge, there is no study exploring the relationship between real remittance inflows and house prices in Kenya, after controlling for other key macroeconomic determinants of house prices. This study addresses this research gap.