Gaps from the cap: Implications for financial inclusion in Kenya - Rogers Ochenge; Samuel Tiriongo (Kenya Bankers Association (KBA), 2018)
This main objective of this paper is to quantify the credit gaps that possibly arose following the introduction of interest rate caps in September 2016 in Kenya. To achieve this objective, we employ two approaches. First, we use a statistical procedure - the HP filter to extract the historical trend over the sample period January 2000 to April 2017 and compute the credit gap as the difference between actual credit and the HP trend. The HP filter indicates that the capping of interest rates led to an average decline of aggregate private sector credit of about 3.5%. Second, is an econometric approach that takes into account other macroeconomic variables that may be important in influencing bank credit extension. The study estimates a credit supply function using a multivariate ARDL model over the period January 2000 to August 2016; just before interest rate capping, then project credit outturn over the period September 2016 to April 2017 conditional on the parameters of estimated ARDL. Similarly, the credit gap is estimated as the difference between the actual credit and the projected trend. On average, the ARDL-based estimates indicate that the interest rate capping led to an aggregate private sector credit decline of about 2.3% (or about Ksh.51 billion). Focusing on sectoral credit, the ARDL-based estimates indicate that household sector experienced a relatively large decline in credit flow of about 5% (or about Ksh.27 billion) while credit to agriculture declined by about 4.9% on average. The credit exclusion of these sectors may have huge adverse implications for financial inclusion both in the short- and long-run. In this regard, there is need to reassess the interest rate law and possibly consider alternative approaches of addressing high cost of credit, which may include enhancing competition among banks.
Keywords: 330; Peer groups; credit score; hidden Markov model; mobile micro credit system; men; women; credit quality and low income earners