MDF results estimates for five countries 2011 - 2017 by Market Development Facility

MDF RESULTS ESTIMATES FOR FIVE COUNTRIES 2011â&#x20AC;&#x201C;2017 Market Development Facility Strategic Guidance Note. 1

Version 2

September 2015

MDF RESULTS ESTIMATES FOR FIVE COUNTRIES 2011â&#x20AC;&#x201C;2017

Market Development Facility Strategic Guidance Note. 1 Version 2, September 2015

Table of Contents TABLE OF CONTENTS..................................................................................................................................................... i ACKNOWLEDGEMENT................................................................................................................................................. iii 1. INTRODUCTION TO THE STRATEGIC GUIDANCE NOTE ON MDF RESULTS ESTIMATESS FOR FIVE COUNTRIES 2011 – 2017................................................................................................................................................................ 1 1.1. Introduction to the Market Development Facility......................................................................................... 1 1.2 Why develop results estimates...................................................................................................................... 1 1.3 Results estimates, projections and actuals.................................................................................................... 2 1.4 Three universal and three intermediary headline indicators along the MDF impact logic............................ 3 1.5 Typical Timeline to Pro-Poor Growth, Jobs and Income................................................................................ 5 2. FACTORS SHAPING COUNTRY STRATEGIES AND VARIATIONS IN THE VOLUME OF RESULTS........................................ 7 2.1 Presence of strong drivers of economic growth (‘growth engines’).............................................................. 7 2.2 Size of the economy, population density and connections ........................................................................... 8 2.3 Maturity and diversity of the private sector, capacity of the public sector.................................................... 8 2.4 Factors influencing job creation..................................................................................................................... 9 2.5 Factors impeding economic activity............................................................................................................... 9 2.6 Implementation window and resourcing....................................................................................................... 9 2.7 The five countries scored against the factors influencing the volume of results......................................... 10 3. MDF RESULTS ESTIMATES FOR FIVE COUNTRIES 2011 – 2017............................................................................ 11 3.1 Business innovations, investment and/or regulatory reform resulting from effective partnerships...........11 3.2 Private sector investment leveraged ........................................................................................................... 12 3.3 Value of Additional Market Transactions .................................................................................................... 14 3.4 Number of jobs created (‘net additional employment’) ............................................................................. 15 3.5 Total effective outreach ............................................................................................................................... 17 3.6 Net additional income ................................................................................................................................. 19 4. CONCLUSIONS: IS MDF ON TRACK TO GENERATING TRANSFORMATIONAL CHANGE IN THE COUNTRIES IT IS ACTIVE?............................................................................................................................... 21

MDF Results Estimates for Five Countries 2011–2017

Acknowledgement This Strategic Guidance note was written for MDF by Mujaddid Mohsin, Harald Bekkers and Victoria Carter. Production and editing was managed by James Maiden.

MDF Results Estimates for Five Countries 2011â&#x20AC;&#x201C;2017

iii

INTRODUCTION TO THE STRATEGIC GUIDANCE NOTE ON MDF RESULTS ESTIMATES FOR FIVE COUNTRIES 2011 – 2017

1.1 Introduction to the Market Development Facility The Market Development Facility (MDF) stimulates investment, business innovation and regulatory reform to create additional jobs and increase the income of poor women and men in rural and urban areas in the IndoPacific region. MDF currently operates in Fiji, Timor-Leste and Pakistan, and expanded to Papua New Guinea (PNG) and Sri Lanka in 2015. MDF negotiates partnerships with strategically positioned private and public sector organisations in its countries of operations. Each partnership is comprised of a tailormade package of activities that enables the partner to innovate, invest and/or undertake reforms in such a manner that small farms and firms benefit from better

access to production inputs, services and end markets. This makes them more productive and helps them grow, which in turn creates jobs and increases income for poor women and men. Each partnership promotes business innovations or reforms, leverages private sector investment or public sector ownership (‘cost sharing’), has a demonstrated link with pro-poor growth, job creation and income generation, and contributes to systemic changes in the economy. MDF seeks to develop partnerships with players in the private and public sector who have the ability to catalyse lasting systemic change that promotes broad-based, sustainable, pro-poor growth.

1.2 Why develop results estimates MDF does not have a traditional log frame, but instead works with a system of initial results estimates or ‘calculated targets’. Estimates are developed by the programme and are typically based on a brief scoping exercise to assess the potential for inclusive pro-poor growth in a country, combined with early indications from the donor regarding budget availability and implementation window. Estimates reflect what is reasonably expected of an investment by MDF in a country and are important tools for communicating expectations to the donor. Additionally, result estimates provide a realistic reference for assessing potential results within a particular country context, i.e. the same investments will yield different results in different countries and estimates help to highlight this point.

Estimates are revised downwards if the basis on which they were developed changes dramatically (e.g. severe economic depression or political instability, cuts to the MDF budget or implementation window or a tougher then expected business environment). Likewise, estimates are revised upwards along with budgets, implementation windows, or when results on the ground are better than expected. Whereas estimates are typically developed before the first partnerships are signed, over time, MDF develops a second set of figures called ‘projections’. Projections are based on a gradually expanding portfolio of partnerships with each signed partnership adding to the projected total. Again projections over time are verified

MDF Results Estimates for Five Countries 2011–2017

and become ‘actual results achieved’. By comparing estimates with projections and actuals one can see whether MDF is ‘on track’ in achieving results – more on this below. This is Version 2 of this Strategic Guidance Note. Compared to Version 1 the following updates were made: 1) estimates were developed for PNG and Sri Lanka; 2) estimates were developed for two new headline indicators, ‘value of additional market transactions’ (intermediary headline indicator) and ‘net additional income’ (universal headline indicator); 3) estimates for Fiji, Timor-Leste and Pakistan were adjusted based on results to date and available budget; 4) estimates were adjusted in line with adjustments to the DCED Standard (longer measurement windows where this is justified) and in line with DFAT conventions (counting adults experiencing meaningful improvements in their livelihoods instead of “units” such as farms or SMEs); 5), estimates were adjusted to factor in certain sectoral multiplier effects and indirect impact (crowding in, copying) in a more realistic manner; and 6) the overall text was updated to reflect experiences to date and to include PNG and Sri Lanka.

Based on this, it is estimated that MDF will measurably improve the livelihoods of over 238,000 poor women and men in five countries between 2011 and 2017, positively impacting the lives of more than 737,000 people including household members. These estimates are based on probable programme resourcing until the end of the current programme phase but some results will continue to be realised two to four years beyond the end of the programme phase.1 This method of estimation is in line with the DCED Standard for results measurement in private sector development. However, for simplicity in reporting, this guidance note captures estimates (against all headline indicators for all countries) and reports on them within the current programme phase. This is calculated based on when partnerships were initiated, for example, some partnerships are initiated later in the programme cycle therefore results will continue beyond 2017.

1.3 Results estimates, projections and actuals MDF follows a three-step process in analysing results. The first step is to develop results estimates, typically based on a brief scoping mission in country, as mentioned above. Estimates are ‘calculated targets’ based on practical matters such as implementation windows (the timeline of the programme work in a country) and budget combined with factors specific to a country such as:  Presence of (strong) drivers of economic growth (‘growth engines’): This influences the appetite for private sector investment and risk-taking and affects the ease in which MDF can find partners to work with, the speed of implementation and, ultimately its scale of effective outreach.  The size of the economy, population density and connectivity: This influences the programme’s ability to reach a relatively significant scale in a certain country.  The maturity and diversity of the private sector, and the capacity of the public sector: This influences the programme’s ability to design larger partnerships (and create larger scale of impact), the likeness of

crowding in to occur (and the scale of crowding in), and the speed of implementation (and timescales). The capacity of the public sector influences the quality of the business enabling environment (and hence private sector speed, appetite for investment, risk-taking and timescale).  Specific factors influencing or impeding job creation and economic activity: These may act as a ‘handbrake’ on activities the programme intends to achieve and limit the scale of implementation and results. For example costs of labour, policy, conflict, political stability, security and environmental risks amongst others. These factors are discussed more detail in Chapter 2 and there is more explanation on how MDF has turned these factors into a system of ‘gears’ to asses the volume of pro-poor growth likely to be generated in a given country. Despite the similar amounts of donor funding over a similar timescale, results between countries can vary significantly. MDF’s result estimates take a first stab at

This version does not yet include results estimates for partnerships to be implemented with funding from the DFAT Gender Equality Fund, which was awarded to MDF in October 2015. 1

MDF Results Estimates for Five Countries 2011–2017

what results may be achieved in each country. They are reviewed and revised periodically, as more becomes known about the different factors influencing the volume of results that can be achieved, as well as any change in design or resourcing. The second step is to develop results projections. This step kicks in when the detailed assessments of growth, poverty and gender at the sector-level are completed and the first partnerships are signed. For each signed partnership a detailed results chain (or theory of change: a logical series of change steps) is developed, based on the specific activities agreed upon in the partnership and the likely changes these will trigger in markets around small farms and firms. All the change steps along the results chain are quantified and it is specified what change is likely to happen by when, and by how much. These quantified (predicted) changes, based on the results chains, which in turn are based on the specific activities agreed upon in a detailed partnership agreement, on insights from the sector assessments,

are labelled results projections. Projections are far more specific than estimates, but are still forward looking. Projections increase as the portfolio of partnerships increases. Projections for each partnership are adjusted based on progress of the implementation of partnerships and are taken ‘off the books’ if the partnership fails or is cancelled. Projections can be aggregated at sectoral and country level. The third step is measuring the actual results (validating projections). As partnerships are implemented all projected results are validated. The actual results achieved are recorded per partnership and are aggregated up to the country level. Comparing actuals with projections (per partnership) and actuals and projections with estimates (per country portfolio) is an important management and learning tool for the programme to understand differences between data sets, progress, and promising avenues to increase results.

1.4 Three universal and three intermediary headline indicators along the MDF impact logic MDF calculates estimates, projections and measures actuals for three intermediary and three universal headline indicators (in addition to many indicators specific to each partnership). MDF measures and aggregates three Universal Impact Indicators outlined in the DCED Standard for Results Measurement in Private Sector Development. Universal impact indicators are measured across partnerships, sectors and countries. They include:  Effective Outreach: This indicator measures the scale of MDF’s impact. In specific cases effective outreach can also include consumers, for example if they benefit from access to better services or labour saving technologies etc. It measures the total number of beneficiaries (small farms, firms and workers) that increase their productivity and/or benefit financially from MDF’s partnerships.2 This includes beneficiaries with income from self-employment activities or those benefitting from additional employment.  Net Additional Employment: This indicator measures the number of jobs generated as a result of MDF’s partnerships. It measures net additional employment

created, calculated in days aggregated into Full Time Equivalent (FTEs) jobs, using 240 working days per year and 8-hour working days.  Net Additional Income: This indicator measures the amount of income generated as a result of MDF’s partnerships. It measures net additional income earned by beneficiaries, calculated as additional income minus additional expenses (converted from local currencies into USD for comparison).3 MDF also measures indicators to show the intermediary results of its portfolio because the timescale of achieving the universal indicators above can be more than two years. These intermediary indicators are also measured across partnerships, sectors and countries and are aggregated for MDF’s whole portfolio. They include:  Number of Business Innovations and Regulatory Reforms: A business innovation can be the introduction of a new product, service, business practice or production method, or the targeting of new suppliers and customers. Innovations can be new to a business, sector or even a country.

Note that this definition is broader than the DCED universal indicator. MDF’s definition includes workers (persons benefitting from the additional employment created). Whereas the DCED definition does not. Consumers are also not included in the DCED definition. 3 Note that MDF’s definition includes net additional income earned by all beneficiaries (small farms, firms and workers) whereas the DCED definition does not include net income earned by workers. 2

MDF Results Estimates for Five Countries 2011–2017

A regulatory reform is a change in the rules and regulations in a country that can reduce transaction costs, stimulate investment and/or open up markets. Some of MDF’s Partnership Agreements may introduce one or possibly multiple innovations and/ or regulatory reforms.  Value of Private Sector Investment leveraged (USD): Measures the amount of money the partner invests in the development and implementation of the innovations or regulatory reform. The investment can be made directly in partnership activities or in further improvements to products or services resulting from a partnership. The investment can be made directly by partners or additional investment leveraged by partners from private funding sources.  Value of Additional Market transactions (USD): Measures the value of additional market transactions generated as a result of MDF’s partnerships. This indicator shows how market transactions are increasing as a result of MDF’s partnerships, representing increased economic activity, which contributes to pro-poor growth. The market transaction is unique to each partnership and depends on the nature of each partnership. The

transaction measured can be taken between MDF’s business partner and beneficiaries, or between MDF’s business partner and its target market, depending on whether each partnership involves market development or enterprise development activities. It measures the payments made between the actors, covering the additional revenue generated from the product or service on behalf of either the partner or the beneficiaries. The indicator is measured at the partner level and measured as revenue, and so should not be confused with net income to beneficiaries or net income to partners. As mentioned, MDF measures many more indicators per partnership, but most of these are specific to a partnership or a sector and/or cannot be aggregated across the portfolio in a straightforward manner. The six intermediate and universal headline indicators were identified because they apply to each partnership regardless of context and can be easily aggregated. In addition to this, the six indicators are strategically located at different levels along the MDF impact logic (see Figure 1 below). The intermediary indicator ‘value of additional market transactions’ was added to the list of headline indicators to fill a ‘gap’ in this regard.

MDF Impact Logic

Figure 1: The Impact Logic for the Market Development Facility

MDF Results Estimates for Five Countries 2011–2017

Innovations introduced and investments leveraged typically correspond with the activity and/or output level, where a partner and MDF design and invest in business innovations together that trigger change in how markets work. Regulatory reform can correspond with the activity and/or output level, but can also correspond with the outcome level, depending on the type of partner and the objective of the partnership. The value of additional market transactions typically corresponds with the outcome level i.e. if outputs were able to trigger changes in how the market works, this can translate into uptake by the market of new products and services, and these new transactions have a commercial value. Effective outreach includes job creation along the value chain (e.g. supply chains and distribution networks) but most beneficiaries are found at the sector-level, where small farms and firms benefit in a measurable manner from better

functioning markets (e.g. higher productivity, increased competitiveness, more sales and better margins). Additional income and additional jobs sit at the goal level and captures increased economic activity for poor women and men through additional employment opportunities and additional money in their pockets (from employment or sales). The strategic positioning of indicators along the MDF impact logic is important for providing a good overview of the programme’s progress. Indicators show actual results at different points in time (intermediary indicators followed by universal indicators) and help articulate the pathway to pro-poor growth. MDF provides an annual update of projected and actual headline indicators (universal and intermediary) for all sector portfolios across all the MDF countries in its Annual Aggregation of Results.

1.5 Typical Timeline to Pro-Poor Growth, Jobs and Income Figure 2 below shows the lifecycle of an MDF partnership and its typical timeline. It also shows the points where results measurement tasks take place and what indicators become available through

TYPICAL TIMELINE

MONTHS 1-3

MONTHS 4-24

Life Cycle of a Partnership

Partnership Signing

Activities Implemented by Parner with Support of MDF

Results Measurement Activities

WHEN INDICATORS BECOME AVAILABLE THROUGH MEASUREMENT

those measurement tasks. As is demonstrated in the diagram, it can take anywhere from 30 to 48 months to create sustainable income earning and employment opportunities to reduce poverty.

MONTHS 24-30

Outputs: Increased Capacity of Partners to Deliver products and services to deliver

Baseline

PROJECTIONS CREATED FOR ALL INDICATORS

INVESTMENT INNOVATION AND REGULATORY REFORM EMPLOYMENT CREATED AT PARTNER LEVEL

Outcomes: Improved Service delivery and uptake in the market

Assessment to verify changes which feed into intervention management

VALUE OF ADDITIONAL TRANSACTIONS

MONTHS 30-48

Purpose: Beneﬁts experienced through increase productivity and sales

Early Impact Assessment measuring impacts

Goal: Increased Income and Employment from businesses working together

Impact Assessment to validate increased income and employment

EFFECTIVE OUTREACH

INCOME AND EMPLOYMENT

Figure 2: Lifecycle of a partnership and timeline of results

MDF Results Estimates for Five Countries 2011–2017

The key factors that determine how long it will take to achieve high-level results include: 1.

The content of a partnership and how long partnership activities take to complete.

How fast the market is able to respond to the improved access to production inputs, services, sales opportunities and regulatory reforms triggered by these partnership activities.

Both factors vary strongly between the different countries in which MDF operates and influence the results. MDF applies a mix of systemic enterprise development (or ‘pre-market development’), systemic market development and regulatory reform to unlock growth in markets that are often very thin. This mix varies between countries and is influenced by several factors explained more in chapter 2. Systemic enterprise development essentially means investing in expanding businesses so that they are able to perform market functions (collection, storage, processing, testing, marketing etc.) that are currently absent. Systemic enterprise development or premarket development is often a necessary ‘first step’ towards market development. These partnerships often entail investments in factory set up, hardware and working capital support, or co-investments with private equity investors. They also require a relatively longer implementation window, with entrepreneurs tending to be less experienced and requiring more business mentoring and on going review, adjustment and support from MDF. Systemic market development has a stronger focus on technical assistance and ‘soft skills’ such as marketing, distribution, sourcing, information, services, etc. The implementation window of these partnerships is relatively shorter; businesses tend to be larger and have relatively stronger management capabilities. Regulatory reform focuses on improving specific aspects of the business enabling environment so as to make specific market systems work better. The implementation window varies.

MDF Results Estimates for Five Countries 2011–2017

In each country MDF implements a mix of these partnership models. In Timor-Leste, for example, MDF’s portfolio will contain partnerships with strong enterprise development or pre-market development features to populate post-conflict economy with first-of-their-kind businesses in processing, manufacturing and tourism. These partnerships will be combined with more typical market development partnership to increase rural distribution and trade and partnerships focused on regulatory reform to open up markets, stimulate investment and reduce dependency on imports. In Fiji a similar mix will be implemented to help diversify the economy away from declining sectors, reduce imports and stimulate new entrepreneurship. In Pakistan, work in the densely populated and well-connected Punjab may resemble market development, whereas work in borderland regions may involve a combination of market development and pre-market development. Also work in urban manufacturing may contain elements of both systemic enterprise development and market development, to develop export markets and localise ancillary industries. MDF negotiates comprehensive partnership agreements around commercially sustainable business cases rather than supporting only particular parts of a business case, such as technical assistance) Depending on the number of activities or change steps negotiated in the agreement, implementation of the agreement can take between four to 24 months. The first uptake by the market of the product or service emerging from these investments can take up to 30 months, depending on factors such as seasonality and/or the novelty and price of the new product or service. The impact of the new product or service on growth, employment and income takes at least a further 12-48 months to materialise, depending on business cycles. MDF’s experience in small island states, post conflict environments and partnerships which introduce ‘first of its kind’ innovations has shown that it takes longer than two years for a business to mature or a product to reach the market in the anticipated form. In such a light, MDF will seek to measure results from partnerships over time periods that are determined by a combination of multiple factors. Again, these timelines are indicative and will vary with relation to specific partnerships.

2/ FACTORS SHAPING COUNTRY STRATEGIES AND VARIATIONS IN THE VOLUME OF RESULTS

The MDF approach could be applied in any country because it’s flexibility allows for the programme in each country to identify the different sectors it should work in (pockets of pro-poor growth), what should be the focus (opportunities to unlock growth), and the types of partners to engage (the most strategic players to unlock pro-poor growth). Every country strategy, inclusive sector growth strategy and partnership are shaped by the country context. In addition, every partnership is tailored to meet the partner’s needs and ambitions. MDF follows the same flexible approach in each country – the same set of analytical steps – zooming in from broad scoping, to inclusive sector-level analyses, to detailed partnership design and negotiations. But despite the same set of analytical steps taking place, each country’s strategy and design is different. The end result is the opposite of the ‘cookie cutter approach’.

The main factors that influence the variations in strategy and initial results estimates between countries are listed below. This is not an exhaustive list. When selecting sectors for an inclusive analysis of growth, poverty and gender other factors are considered such as relevance for the poor, Women’s Economic Empowerment (WEE), the influence of government (good or bad regulations and stimulating or disruptive subsidies) and existing donor activities in the sector. Also considered are the influence of other non-economic factors and actors, and to what extent the market systems approach is equipped to tackle the problems it is encountering (feasibility). The factors below sit above these and provide the entry points for ‘big picture’ analyses.

2.1 Presence of strong drivers of economic growth (‘growth engines’) Economic growth is, among others, a function of growing demand (in domestic or export markets), gaps between existing demand and supply, and the amount of money circulating in the economy and the private sectors ability to respond to investment needs. Where demand is strong and there is sufficient investment capital, economic growth can more easily take root. The five MDF countries are very different in this regard. PNG and Timor-Leste enjoys strong economic growth fuelled by investments in extractive industries and public spending. There is strong domestic demand, which is currently mostly met through mostly expensive imports. Connecting this domestic demand to local production –

substituting for imports in the process – can be a strong driver of more inclusive and more balanced economic growth. Local entrepreneurship will need to be built up in the process; there is some investment capital floating around, but access to business services is limited. Pakistan is not achieving the growth potential of some of its South Asian neighbours and is not growing fast enough to have an impact on reducing poverty levels. This is due to a range of factors such as the prevalence of a relatively traditional trading system, a relatively small industrial base (with a few large players), relatively less foreign investment and the relatively high costs of doing business. There is scope to increase exports; there is

MDF Results Estimates for Five Countries 2011–2017

scope to improve connections between the rural areas and the growing cities (to give rural customers access to better production inputs and services, and urban customers to better quality products); and there is scope to broaden the entrepreneurial base and support new business models, but access to capital is an issue. Fiji’s economic growth is low as its traditional growth engines – sugarcane, copra and garments are in decline or went through significant restructuring. Fiji needs to diversify its economy and support new and existing entrepreneurship around new growth engines. Access to capital is an issue. There is scope to ‘localise’ more in the growing tourism sector through the locations tourists visit and activities they do, what they buy and eat. There is scope to develop niche exports markets for

‘Fijian’ products; and there is scope to reinforce Fiji as an offshore processing base (catering to sub-contracted manufacturing or business process operations). Sri Lanka, finally, is experiencing a post-conflict boom with an increasing urban demand for products and services and increasing tourist arrivals. At the same time, the country needs to find new export growth drivers now that the garment industry is consolidating, and there is a need to rebuild parts of the economy in the North and the East of the country. There is scope to increase exports in agriculture, aquaculture and, possibly ICT. There is also scope to support entrepreneurship where strong demand (from tourist and urban consumers) has created demandsupply gaps. Access to capital is also an issue in Sri Lanka.

2.2 Size of the economy, population density and connections In addition to the economic pace in each country, the volume of results also depends on the size of the economy and the number of people (producers, businesses, workers, and consumers) active within it. To a lesser extent, the relative dispersion or concentration of these actors can also impact volume of results. Partnerships in large and more densely populated and well-connected countries are likely to have, on average, a much larger effective outreach than partnerships in countries that are smaller, less populated or more fragmented. In this regard, the five MDF countries are very different. Fiji has around 65,000 farming households whereas

Pakistan has tens of millions. One intervention in agriculture in Pakistan my have a larger effective outreach than all rural households in the whole of Fiji combined. Within Pakistan there will be substantial differences between the densely populated Punjab region and more isolated border regions, which feel surprisingly ‘island-like’ in terms of size and connections. PNG and Timor-Leste have densely populated urban pockets and dispersed rural pockets – all not well connected. Sri Lanka, finally, is considerably bigger than Fiji and much better connected than Timor-Leste, but of course lacks the scale of Pakistan.

2.3 Maturity and diversity of the private sector, capacity of the public sector The capacity of private and public sector partners is perhaps the most important factor impacting the volume of results. Their presence, maturity and variety strongly influence the speed and scale of implementation. In Timor-Leste businesses are few and predominantly small, young, local and to a degree dependent on government contracts – the picture of a young nation finding its feet after years of conflict. PNG features a mix of private sector players, with small and inexperienced businesses being the majority. In Fiji the scenario is more balanced, with smaller, younger and mostly

MDF Results Estimates for Five Countries 2011–2017

local businesses leading the charge in diversifying the economy, but also with some larger, more established local business playing a role. Pakistan’s economy is as diverse as the country itself with a gamut of large and small local and international businesses, but also with a clear need to have more (new) businesses to fill gaps in the economic fabric. The same applies for Sri Lanka. There is room for improvement in the functioning of the public sector in each country. There are differences between countries such as Pakistan and Sri Lanka – where improvements in performance would come

from a focus on playing a more appropriate role in the economy with efficient procedures, and PNG and TimorLeste – where basic public sector capacity development is important in addition to improved performance and appropriate roles. Fiji’s public sector occupies the somewhere in middle ground here. For the private sector, in countries such as Timor-Leste and PNG, partnerships are more likely to be with smaller,

newer businesses, with more time and resources going towards ‘making these businesses work’ – resulting in less effective outreach per business. In Fiji there will be a mix of smaller and larger partnerships. Partnerships in Sri Lanka and Pakistan are more likely to gravitate towards larger more established companies, with more energy going into ‘making markets work’ (and thus a bigger effective outreach to small farmers and entrepreneurs).

2.4 Factors influencing job creation Unemployment rates, labour costs, labour laws, their implementation (or lack of), the availability of (under) utilised family labour and the overall make-up of the economy all influence the extent to which growth creates employment or results in ‘job-less growth’. In Timor-Leste, PNG and Fiji, labour is significantly more expensive than in Sri Lanka or Pakistan. Whereas in Pakistan increase in agricultural production is likely to create much additional employment, in Fiji, Timor-Leste

and PNG it may lead to increased mechanisation and not as much employment. In Sri Lanka an increase in agriculture is likely to generate ‘mixed’ results: more employment, but also more mechanisation. In countries such as Pakistan, and to a lesser extent Sri Lanka, each partnership is likely to create substantially more jobs than in Fiji, PNG or Timor-Leste (which is compounded by the small size of businesses and smaller outreach mentioned above).

2.5 Factors impeding economic activity Conflict, political instability, lack of contract enforcement, security risks, environmental risks, adverse trade and taxation regimes, and the absence of infrastructure and utilities all negatively influence the pace of the economy. All countries in the MDF portfolio struggle with some of these issues. Either they may be small island economies

facing high transportation costs and strict quarantine measures, emerging out of conflict, or they are struggling to contain political instability. Pakistan, PNG, and TimorLeste are in a slightly more disadvantageous position in the face of these challenges compared to Fiji and Sri Lanka.

2.6 Implementation window and resourcing Finally, the implementation window and resourcing also influence the volume of results. Results are not produced evenly over the duration of a programme, but escalate over time and are concentrated in the latter half of the programme (years three and beyond). Partnerships need time to be well researched, designed and negotiated and the results emerging from them need time to mature. Overall, a longer implementation window is relatively more efficient for a programme than something shorter (e.g. 2-3 years). Once the initial assessments are

complete, it allows for more time to build up a portfolio of partnerships, learn from what works, stimulate crowding (if that is realistic to expect), and move to higher-order cross-sectoral constraints affecting a range of sectors to ultimately achieve truly transformative, systemic changes in the economy. The first signs of this change start after around two to four years. However, it typically takes at least eight years and more likely twelve to fifteen years for systemic change to establish itself fully.

MDF Results Estimates for Five Countries 2011–2017

Resourcing also influences results – the more partnerships, the more results. But the time factor is also important. Partners and sectors ‘absorption capacity’ for change is limited, i.e. there are only so many partners ready to invest in change, and when they do, it takes time to absorb that change. With larger budgets, a programme should be able to work in more sectors of the economy

or, have a sufficiently long implementation window to build up the portfolio over time. Fiji has the longest implementation window of six years; Timor-Leste and Pakistan have reasonable windows of 4.5 and 3.5 years respectively; PNG and Sri Lanka will have just started to produce results when the current 2011 to 2017 contracting period for MDF ends.

2.7 The five countries scored against the factors influencing the volume of results Table 1 below summarises how the different countries in the emerging MDF portfolio compared against the factors listed above. Table 1 – Countries in the MDF portfolio compared against results factors

Fiji

Timor-Leste

PNG

***

Size of the economy and population density

****

***

****

***

****

***

Job creation Factors impeding economic activity (= minus) Implementation window

NB: The maximum ‘score’ is five stars (*****), the minimum score is one star (*)

Sri Lanka

Drivers of economic growth

Maturity and diversity of the private sector

Pakistan

MDF Results Estimates for Five Countries 2011–2017

3/ MDF RESULTS ESTIMATES FOR FIVE COUNTRIES 2011 – 2017

3.1 Business innovations, investment and/or regulatory reform resulting from effective partnerships Every effective partnership between MDF and a partner in the private or public sector will result in business innovation or regulatory reform relevant for triggering sustainable and broad-based, inclusive growth in a country. Some partnerships will contain innovation or reform relevant for the country (e.g. a ‘first-of-its-kind’ investment), some will contain the same for a sector, and sometimes the innovation is particularly relevant for a specific partner (for example, a partner that for the first time applies a certain technique in a particularly challenging part of the country never tried before). One partnership can contain more than one innovation (e.g. a partnership could aim to disseminate new agricultural information to farmers via an equally new and untested channel). It is not desirable to categorise or predetermine which innovations or reforms MDF should promote. This should be driven by the country context and the partner’s agenda. But it is possible to estimate the number of innovations and reforms likely to be generated over time. The main factors determining how much innovation and/or reform can be achieved are: 1) the length of the implementation window and resourcing, and 2) the maturity and diversity of potential partners. Note that there is likely an inverse relationship between the maturity of partners and the maturity of the economy overall, and number of innovations (complexity) per partnership. The more mature and diverse the economy, and the more mature the partner, the more likely that small change steps are sufficient for the partner to trigger change in markets. Conversely, the less mature and diverse the economy, the less mature the partner, the more needs to be done by the partner to make things work.

MDF’s partnerships in Timor-Leste are likely to be among the smallest, but also among the most innovative, and the toughest to implement. The partner may have relatively less skills to handle change while they cannot lean as much on the existing business environment. For example, there may be no one importing the machines needed, or be able to train staff on how to use them. There may be little storage and logistics available to bulk and ship produce from the regional areas to the factory. There may be no detailed information available about where to source materials or produce. There may be no good packaging material available and retailing may need to be set up from scratch. Therefore the number of partnerships, the average number of innovations/reforms per partnership, the average financial investment per partnership, and how long it takes to implement them will vary considerably per country. In some countries, MDF is more likely to resort to more but smaller partnerships, whereas in other countries to fewer but larger partnerships. Partnerships and subsequent innovations/reforms are not evenly distributed between years. As mentioned already, the first year is spent on analysing the economy, building up the capacity of the country team, building up a network of potential partners and starting negotiations, resulting in the first signed ‘deals’. In the second year the programme begins to take off with more partners on board, and from the third year the programme moves into a mature level of implementation. Table 2 shows the average realised and estimated number of innovations and reforms per country per year.

MDF Results Estimates for Five Countries 2011–2017

Table 2 – Realised and estimated number of innovations and reforms per country per year*

Country

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

2016-2017

TOTAL

Fiji

Timor-Leste

0**

Pakistan

Sri Lanka

PNG

*Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. **MDF Timor-Leste will not be adding any new partnerships in FY 2016-2017 due to constraints around resourcing. No new innovations will be added to the portfolio.

Since initial MDF results estimates, partnership numbers, and to an extent innovations, for Fiji and Timor-Leste have been scaled down. In Fiji the original estimated number of partnerships was higher as it reflected the expectation that MDF would be working with a large number of relatively smaller partnerships. After several years of engagement, partnerships on average are bigger than expected with more innovations, investment, and outreach, but are also more complex in nature. Partnerships have taken longer to implement. The total number of estimated innovations and reforms are reduced from 85 to 75 in Fiji. In Timor-Leste, the current budget allocation is significantly lower than what the initial design called for and MDF has scaled back drastically on the number of partnerships that can be signed on (from around 45-65 to less than 20). This is despite the high level of interest and response from the Timorese private sector. Like in Fiji, the average number of innovations investments, and outreach per partnership is higher than originally expected, but this cannot offset the significant reduction

in the number of partnerships. For the total number of estimates innovations and reforms are reduced from 65 to 26. For Pakistan, the number of partnerships to be implemented is still in line with expectations, but the number of innovations and reforms is higher than expected. The estimated total number is adjusted upward from 40 to 51. It should be noted that, as potential partners are more sophisticated (and more in number) when compared to Fiji and Timor-Leste, the number of innovations/reforms introduced per partnership is generally less. This reinforces earlier analyses by MDF that in relatively more developed economies like Pakistan, small changes introduced into the market (through individual partners) can elicit relatively larger impact. For Sri Lanka and PNG, estimates for innovations and reforms introduced per partnership were completed using Pakistan and Timor-Leste as proxies respectively.

3.2 Private sector investment leveraged Partnership agreements MDF negotiates contain intervention plans in which both the partner and MDF invest. ‘Investments leveraged’ are the financial contributions from the partners to these action plans. The investment volume per partnership agreement is predominantly influenced by: 1) the partner’s size and maturity (it is not sustainable to ‘overinvest’ in a small partner), and 2) the scope of the partnership (bigger partners in bigger countries can handle bigger budgets),

MDF Results Estimates for Five Countries 2011–2017

and 3) the type of investment needed (investments in market development depend more on relatively cheaper technical assistance while investments in enterprise development depend more on relatively more expensive investments in hardware). Other factors are not expected to play a significant role: in each country, with each partner, MDF negotiates a sustainable costsharing arrangement factoring in the prevalent economic conditions.

In Fiji, MDF is working with a mix of larger and smaller partners and a mix of activities. Some are geared toward market development, some towards enterprise development. In Timor-Leste the partnerships are usually smaller, with more efforts going into setting up and growing these small businesses. PNG is expected to be similar to Timor-Leste in this regard. In Pakistan there is more scope to strike bigger (but relatively cheaper) deals with bigger partners, more geared towards market development activities. At the same time, working with smaller partners in a more enterprise development manner to promote innovation or to increase connections with business in distant regions has been more important than initially anticipated. Sri Lanka is expected to be comparable with Pakistan. Like in Pakistan, in addition to the bigger partnerships, enterprise development with smaller partners will be important in the conflict-affected North and East of Sri Lanka. Table 3 shows the average realised and estimated investments leveraged per country per year. For Fiji, Timor-Leste and Pakistan averages are reflective of the implementation experience so far.  For Fiji the average investment leveraged per partnership was revised upward from USD 53,000 to USD 69,000 per partnership.

 For Timor-Leste the average investment leveraged was revised upward from USD 33,000 to USD 46,000 per partnership.4  For Pakistan the average investment leveraged was revised downward from USD 75,000 to USD 54,000 per partnership.  For Sri Lanka and PNG, average investments leveraged of USD 54,000 and USD 46,000 respectively were being used in developing estimates. These figures were chosen on the basis of similarities shared by Sri Lanka with Pakistan and PNG with Timor-Leste. These estimates will be improved once the early partnerships are signed in Sri Lanka and PNG. Please note that estimates are based on averages per partnership; the actual amounts generated per partnership differ substantially from one partner to the next. Also, investments for partnerships particularly for those signed at the later stages of the programme in each country will spill over to years beyond programme end date. The table below follows a simplified format, whereby the investments leveraged shown are based on the partnerships signed per year up to the last year of the current MDF contract date of 2017.

Table 3 – Realised and estimated investment leveraged per country per year (USD)*

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

2016-2017

69,000

137,000

1,029,000

892,000

686,000

3,499,000

Timor-Leste

46,000

448,000**

414,000

138,000

0***

1,046,000

Pakistan

164,000

601,000

765,000

655,000

2,185,000

Sri Lanka

270,000

648,000

918,000

PNG

230,000

460,000

690,000

Country Fiji

TOTAL

* Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. All figures are rounded to the nearest thousand. ** This figure includes the investment leveraged from the Balibo House Trust for the Balibo Fort Hotel. *** As MDF Timor-Leste is not able to sign any new partnerships in FY 2016-2017, no additional investments from private sector partners can be leveraged.

This average investment per partnership does not include the investment leveraged by MDF on its tourism partnership involving the Balibo Fort Hotel. The investment leveraged for this partnership is higher than the country average by several factors (Balibo House Trust was able to mobilise an investment figure of USD 310,000 for the partnership). Such investment levels are unlikely to be seen for other partnerships in Timor-Leste. Thus, this investment figure has been excluded from the average as it distorts the picture significantly. 4

MDF Results Estimates for Five Countries 2011–2017

In Fiji and Timor-Leste, investments leveraged per partnership exceed initial estimates. This reflects a more ‘entrepreneurial spirit’ present in these countries than some analysts had predicted beforehand, but also reflects the need to invest more in more complex business models in order to make markets work. However, in Fiji higher investments per partnership do not balance out a slower than expected pace of implementation due to this complexity and the total investment leveraged will be closer to USD 3.5 million, instead of USD 4.5 million previously estimated. In Timor-Leste, even MDF’s role in providing seed capital for a large investment such as the Balibo Fort Hotel cannot compensate for the overall lack of resourcing.

Thus total investment leveraged in Timor-Leste will be closer to USD 1 million instead of USD 2 million previously estimated (MDF in Timor-Leste was on track to surpass this previous estimate with adequate resourcing). In Pakistan it is too early to tell how the mix of partnerships in terms of scale and market development versus enterprise development will turn out. Nevertheless, based on early implementation experience, estimates have been adjusted downward. It should be noted that overall, MDF generates very high investment ratios in which the investments by the private sector exceed the investments by MDF.

3.3 Value of Additional Market Transactions The net value of Additional Market Transactions (AMT) gauges the response of the market to new or existing products or services and the ‘uptake’ of the market before the final impact in the sector on poor women and men can be measured. The indicator shows by how much market transactions are increasing as a result of MDF partnerships, and is represented in terms of increased economic transactions in USD. The greater the amounts of additional market transactions, means more people are involved in buying the new product or service, and the potential effective outreach is higher. But also stronger market uptake and higher value of AMT, proves that the new product or service is filling a real gap in the market and it is more likely that the business model supported by MDF will sustain itself in the long run. Thus AMT as an intermediary indicator sits ats an important junction between the innovation supported by MDF and the impact of that innovation on target beneficiaries. It is an important indicator for the viability of the innovation promoted as well as the effective outreach it is likely to have.

also not included in the first version of this estimates guidance note). To estimate AMT, MDF uses the analogy of a system of ‘gears’ (also known as country coefficients, or ‘levers’). These are informed by the implementation experience to date. The gears indicate the value of business transactions expected on the basis of the investments made. A higher gear indicates more business transactions per dollar invested; a lower gear means less business transactions per dollar invested. Note that business transactions do not equal profits. In a very large yet very competitive economy additional investments may generate significant additional transactions, but relatively less profits as margins per transactions are low. Conversely, in a small yet not very competitive economy a few additional transactions may generate significant profits as margins are high.

In the country context, the net value of AMT is likely to be influenced by 1) the drivers of economic growth, 2) the size of the economy, population density and connectivity, and 3) the maturity of the partners MDF can work with (including their ability to invest and handle scale). In short, the market transactions indicator exhibits a strong correlation to the pace of the economy, i.e. is there a drive to invest and grow? Is there space to grow? And are there partners who have capacity to utilise that space?

Fiji and Timor-Leste are expected to be on one end of the spectrum, operating in ‘first gear’. Fiji needs to diversify its economy as traditional sectors have become stagnant. Timor-Leste, while facing very rapid growth in recent years, needs to develop true private sector growth, which is not dependent on government contracts. Pakistan and Sri Lanka are on the other end of the spectrum, operating in third (Sri Lanka) and fourth (Pakistan) gears driven by a more mature private sector, strong demand and larger domestic markets. MDF expects the value of AMT to be several times higher in Pakistan and Sri Lanka as compared to Fiji and Timor-Leste. The estimated value of AMT in PNG is expected to be somewhere in the middle, operating in second gear driven by a relatively larger country, strong growth, but a weak private sector.

Estimating the value of AMT is more difficult than the other two intermediary indicators (and for this reason

The estimated AMT for Fiji has been used as the base for estimating AMT for all the other MDF countries. The

MDF Results Estimates for Five Countries 2011–2017

method of estimation capitalises on the relationship that exists between return on investment (ROI) and net profit margins for any given investment. For Fiji, a 10% ROI and a 20% profit margin was assumed. Consequently this base AMT value (or the AMT in Fiji) was multiplied with the respective country coefficients, and adjusted to each countries anticipated private sector investment leveraged levels to derive (per year) estimates of AMT for all MDF countries. Please note that as country experiences in Pakistan, Sri Lanka and PNG deepen for MDF, this methodology will be revisited and the gears (or coefficients) adjusted accordingly. Based on this methodology and the implementation experiences in Fiji and Timor-Leste, the early experiences in Pakistan – and how this could compare to Sri Lanka and PNG – the following estimates were developed:  For Fiji, the average AMT value is estimated at USD 69,000 per partnership.

 For Pakistan, the average AMT value is estimated at USD 270,000 per partnership.  For Sri Lanka, the average AMT value is estimated at USD 162,000 per partnership.  For PNG, the average AMT value is estimated at USD 93,000 per partnership. Table 4 shows the average realised and estimated AMT value per country per year. Please note that estimates are based on averages per partnership; the actual amounts recorded per partnership can differ substantially from one partner to the next. Also, market transactions for partnerships, particularly those signed at the later stages of the programme will spill over to years beyond programme end date. The table below follows a simplified format, whereby the value of AMT shown is based on the partnerships signed per year up to the last year of the current MDF contract date of 2017.

 For Timor-Leste, the average AMT is estimated at USD 46,000 per partnership. Table 4 – Realised and estimated value of additional market transactions generated per country per year (USD)*

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

2016-2017

69,000

137,000

1,029,000

892,000

686,000

3,499,000

Timor-Leste

46,000

184,000

414,000

138,000

0**

782,000

Pakistan

810,000

2,970,000

3,780,000

3,240,000

10,800,000

Sri Lanka

810,000

1,944,000

2,754,000

PNG

467,000

933,000

1,400,000

Country Fiji

TOTAL

* Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. All figures are rounded to the nearest thousand. ** Since MDF Timor-Leste will not be adding any new partnerships in the last year due to current resources, no additional market transactions are attributed to the last year.

3.4 Number of jobs created (‘net additional employment’) MDF measures the net additional employment created from the investment, business innovation and regulatory reform unlocked through MDF partnerships. MDF defines job creation as the number of net additional full-time equivalent (FTE) jobs created, with 240 days of paid labour per year equalling one FTE. This formulation is contextually appropriate in the economic contexts that MDF operates in, as many jobs created would be part-time. In order to reconcile full and part time job

opportunities and report in a coherent and consistent manner, MDF reports it in terms of FTE. For example, two part-time jobs, each for 120 paid days per year, together are reported as one FTE. Each FTE job created will be counted as ‘1’ and counted only once (also if it exists year after year). But the rewards from additional employment will be calculated for two business cycles (see more on this below).

MDF Results Estimates for Five Countries 2011–2017

The number of jobs created is expected to be primarily influenced by 1) the size of the economy 2) the size and maturity of the partner, 3) factors impeding economic activity, and 4) the situation on the labour market and factors impeding job creation (levels of unemployment, cost of labour, labour laws etc.).

the job figures are reflective of the implementation experience so far, including the relevance of longer measurement windows for partnerships that take longer to mature, the relevance of sector multipliers (notably in tourism) and a realistic assessment of the likeliness of indirect impacts (crowding in, copying) to occur:

Fiji shows a scenario in which a limited number of mostly full-time jobs are created as a result of businesses investing in expansion. Seasonal work is less significant and an increase in agricultural productivity generates more employment but also stimulates mechanization due to labour shortages. In Timor-Leste the number of full-time jobs in expanding businesses is less (most businesses are smaller), but there is expected to be more scope in other jobs around agriculture (e.g. through service providers and distribution). However, in Timor-Leste the cost and availability of labour may push farmers to consider mechanisation where possible. PNG is expected to exhibit similar issues around jobs as Timor-Leste with the cost of labour and the size and maturity of partners restricting the expected number of jobs created per partnership. Pakistan and Sri Lanka are again expected to be at the other end of the spectrum. In Pakistan there is potential for substantial job creation in agriculture and manufacturing. In Sri Lanka job creation is expected to be significantly higher than Fiji, Timor-Leste and PNG, but less than Pakistan. Less unemployment, less casual labour, higher levels of education and higher wages will result in relatively more full-time jobs and more investments in mechanisation.

 For Fiji the average job creation figure per partnership was revised upward from 13 FTE to 28 FTE per partnership. (NB: job creation through the partnership with Standard Concrete Industries is weighted very conservatively).

Table 5 shows the average realised and estimated job creation per country per year. For Fiji and Timor-Leste,

 For Timor-Leste the average job creation figure per partnership was revised upward from 13 FTE to 20 FTE per partnership.  For Pakistan the average job creation figure was increased from 150 FTE to 195 FTE per partnership.  Early estimates for jobs created per partnership for Sri Lanka and PNG were based on (but are not the same as) averages for Pakistan and Timor-Leste respectively. Note that estimates are based on averages per partnership. The actual amount created per partnership differs substantially from one partner to the next. Also, job creation for partnerships, particularly those signed at the later stages of the programme in each country will spill over to years beyond programme end date. The table below follows a simplified format, whereby the FTEs shown are based on the partnerships signed per year up to the last year of the current MDF contract date of 2017.

Table 5 – Realised and estimated job creation per country per year (FTE)*

Country

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

2016-2017

420

364

280

1,430

Timor-Leste

180

0**

340

Pakistan

585

2,145

2,730

2,340

7,800

Sri Lanka

600

1,440

2,040

PNG

105

210

315

Fiji

TOTAL

* Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. All figures are rounded to the nearest full number. ** As MDF in Timor-Leste will not add any new partnerships to the portfolio in FY 2016-2017, no additional FTE jobs are shown for that year.

MDF Results Estimates for Five Countries 2011–2017

In Fiji, total jobs creation exceeds initial estimates, despite less partnerships being implemented. More jobs (and more complexity) per partnership more than balance out a slower than expected pace of implementation. In Timor-Leste job creation per partnership also exceeds initial estimates, but due to

limited resources total FTE creation will be relatively modest. In Pakistan, the portfolio is still very young. Some strategic partnerships being added to the portfolio soon are expected to raise the average jobs created per partnership significantly.

3.5 Total effective outreach Effective outreach refers to the number of working adults – family members running family-run farms and SMEs, workers, and occasionally consumers – who experienced a real, tangible, measurable change in income either through more or better-paid employment, selling more or with better margins, or they could save money from being able to use more efficient equipment or better services. It is important to be clear on how MDF defines effective outreach. First, there is the distinction between outreach and effective outreach. Outreach refers the number of individuals ‘reached’ or ‘touched’, for example those who were exposed to new information, a new service or new technology. However, if they are not able to use this to their advantage the outreach is not ‘effective’ i.e. it did not change anything. It is possible for any programme to have very high outreach but very little effective outreach. Different partnerships typically have different profiles in this regard. Media interventions often have a massive outreach but only a small portion will turn to effective outreach (e.g. not everyone is able to or will make changes for the better based on a radio message, especially if the change proposed is not easy, requires multiple steps, or lacks ‘do or die’ urgency). Conversely, small, targeted partnerships in which a few suppliers are intensively trained and coached will have very little outreach to start with, but a much higher percentage of that outreach will be effective. Because different market problems require different solutions through different channels, one model is not better than the other. MDF works through a variety of channels. Because there is are great differences between partnerships and because outreach (non-effective) can be perceived as an ‘empty’ indicator, MDF reports only on effective outreach. Secondly, effective outreach also does not include the wider group of people who benefit in indirect ways,

for instance as a result of more money being available in the household or extended family for education and healthcare. MDF reports effective outreach as the number of working adults who themselves experienced a measurable change in income due to themselves experiencing changes in the way markets work around them as a result of MDF partnerships. However, it is understood that these individuals are income-earning members of their households or extended families and support a number of dependents. The formula used for estimating total effective outreach is:  Family members running family-run farms and SMEs who experienced an increase in income +  Consumers benefitting from savings in income: +  All workers benefitting from increased employment opportunities (full-time or part-time, or increases in salary) Where there is no reliable date to estimate how many workers on average will occupy one FTE job, it is conservatively assumed that two workers will occupy one FTE job.5 In reality this is likely to be more, particularly in countries such as Pakistan where labour is cheap and part time or seasonal jobs are more common than formal/contractual jobs. Factors influencing job creation were discussed earlier. Factors influencing effective outreach to self-employed small farms and firms is expected to be primarily influenced by 1) the size of the economy and population density, 2) the size and maturity of the partner, and 3) factors impeding economic activity (as these three together influence the scope/outreach of the intervention).

Thus far there has not been an opportunity to validate this conservative assumption. As results start coming in for Fiji and Timor-Leste, a validation exercise will be initiated to see how much outreach one FTE job is contributing to. 5

MDF Results Estimates for Five Countries 2011–2017

In Fiji and Timor-Leste, partnerships are expected have relatively smaller outreach. In PNG, average outreach is estimated to be slightly larger, based on the population size and concentration in particular locations in the country. In Sri Lanka outreach is estimated to be significantly larger than PNG, but at the same time significantly smaller than in Pakistan. It should be noted that outreach could be significantly more in countries such as Pakistan and Timor-Leste if there would be less uncertainty about the political stability in the country and the security situation as this act as a deterrent for investment).

outreach to consumers will be added later. (NB: In these figures the outreach of Standard Concrete Industries is weighted very conservatively). .  For Timor-Leste the average effective outreach per partnership to small farms and firms was revised upward to 510 per partnership. Nevertheless, these figures are relatively conservative and include the conservative estimate of two workers occupying one FTE job. In reality this number will be higher. Where applicable, effective outreach to consumers will be added later.

Table 6 shows the average realised and estimated outreach per country per year. Estimates are reflective of the implementation experience thus far, including the relevance of longer measurement windows for partnerships that take longer to mature, the relevance of sector multipliers (notably in tourism) and a realistic assessment of the likeliness of indirect impacts (crowding in, copying) to occur. Also, for self-employed household MDF shifted from counting ‘units’ (farms, SMEs) to the number of family members running these family businesses. This brings MDF more in line with other (DFAT-funded) programs and makes the count more consistent: adult (self-employed) workers and consumers instead of combining this with farms and SMEs.  For Fiji the average effective outreach per partnership to small farms and firms was revised upward to 557 beneficiaries per partnership. These figures include the conservative estimate of two workers occupying one FTE job. In reality this number will be higher. Where applicable, effective

 For Pakistan the average effective outreach per partnership was adjusted upwardly to 4,200 beneficiaries. The average seen in the current portfolio of partnerships is lower than this estimate. However, as a large proportion of results from the portfolio are still to come, the average is expected rise. These figures include the conservative estimate of two workers occupying one FTE job. In reality this number will be higher. Where applicable, effective outreach to consumers will be added later. Note that estimates are based on averages per partnership. The actual amounts per partnership differ substantially from one partnership to the next. Also, effective outreach for partnerships, particularly those signed at the later stages of the programme in each country will spill over to the years beyond programme end date. The table above follows a simplified format, whereby the effective outreach shown is based on the partnerships signed per year up to the last year of the current MDF contract date of 2017.

Table 6 – Realised and estimated total effective outreach per country per year *

Country

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

557

1,114

8,355

7,241

5,570

28,407

Timor-Leste

510

2,040

4,590

1,530

0**

8,670

Pakistan

12,600

46,200

58,800

50,400

168,000

Sri Lanka

7,380

17,712

25,092

PNG

2,680

5,360

8,040

Fiji

2016-2017

TOTAL

*Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. All figures are rounded to the nearest whole number. ** As MDF in Timor-Leste will not add any new partnerships to the portfolio in FY 2016-2017, no additional effective outreach is shown for that year.

MDF Results Estimates for Five Countries 2011–2017

In Fiji effective outreach exceeds initial estimates despite less partnerships being implemented. Higher levels of complexity and results per partnership more than balance out a slower then expected pace of implementation. Effective outreach is expected to increase modestly if the actual number of workers per FTE job will be included. In Timor-Leste effective outreach

per partnership also exceeds initial estimates. However, due to limited resources total effective outreach will be modest. Effective outreach is expected to increase modestly if the actual number of workers per FTE job will be included. In Pakistan, the portfolio is young and the average effective outreach per partnership is expected to increase.

3.6 Net additional income MDF measures the net additional income that small scale farmers, firms and workers earn, and the savings that consumers generate from better functioning markets and better access to clients, to production inputs, equipment and services, and to job opportunities. As with all other indicators, only additional income that is attributable to MDF partnerships is reported. Typically in market systems programmes, income increases are measured for two business cycles (e.g., two tourist seasons, two agricultural seasons) or two years where such seasonality does not apply. However, MDF’s experience in small island states, post conflict environments and partnerships which introduce ‘first of its kind’ innovations has shown that this rigid definition of a results time line do not apply. In many cases, it takes longer than two years for a business to mature or a product to reach the market in the anticipated form. In such a light, MDF will seek to measure additional incomes from partnerships over time periods that are determined by a combination of: (1) business cycles, (2) seasonality, and (3) product/ service cycle (e.g. income benefits achieved by farmers using seedlings for crops that take three3 years to mature). As with all other indicators, the strategy for measuring additional income impacts will vary and will be customised to specific partnerships. Generating net additional income is dependent on all factors listed in Section 2. These include 1) a presence of drivers of growth that creating strong demand, which in turn translates into higher margins and demand for larger volumes; this is amplified by 2) the size of the economy (larger transactions); and in turn by 3) the maturity and diversity of the private sector and the capacity of the public sector (to open up markets so demand and supply can interact). At the same time, factors dampening economic activity for job creation will also resonate at this level. Finally, significant changes in income levels for large numbers of poor women and men depend on a large portfolio, which in turn depends on sufficient resourcing and a sufficient implementation window. In short, all

factors influencing economic activity and outreach accumulate in the volume of net additional income generated. In MDF, a 15% increase in net additional income for poor women and men is held as the key criteria for considering outreach as being “sufficiently effective” (i.e. the change in income is meaningful for improving livelihoods). This is stipulated in the MDF design. MDF aims to increase the incomes of the poor women and men it is reaching by at least 15%. However this methodology is only applied in the early stages of a country programme in the absence of a significant portfolio of partnerships, or actual results. As partnerships in MDF countries start to yield actual results, this 15% measure is replaced by actual additional incomes generated. For example, the estimated values shown below in Table 7 include estimates for Fiji, TimorLeste, and Pakistan based on actual additional incomes measured from currently active partnerships. Since partnerships have not yet been put in place for MDF in Sri Lanka and PNG, the additional income estimates are still using the 15% increase in incomes as the benchmark. The estimates shown below in Table 7 should be considered as threshold values, which MDF aims to surpass. The 15% increase is calculated for each MDF country with respect to the national poverty lines. For example, in Sri Lanka where the national poverty line is equivalent to USD 0.98 per day per capita, an annual net additional income increase of USD 53 per beneficiary can be considered as “sufficiently effective”. For developing estimates for net additional income increase in any other MDF countries, the same methodology will beis used, based on the relevant poverty lines per country, and eventually replaced by actual additional incomes data. Table 7 shows estimates for net additional incomes per country per year. For Fiji, Timor-Leste and Pakistan, actual average net additional income increase measured per beneficiary is used to calculate estimated incomes over the lifetime of the programme. As there are no actual measurements of net additional incomes per beneficiary in Sri Lanka and PNG, a 15% increase over individual

MDF Results Estimates for Five Countries 2011–2017

country poverty lines have been used. Note that estimates are based on averages per partnership. The actual amounts per partnership differ substantially from one partnership to the next. Also, income generation for partnerships, particularly those signed at the later stages

of the programme in each country will spill over to years beyond programme end date. The table below follows a simplified format, whereby the net additional income shown is based on the partnerships signed per year up to the last year of the current MDF contract date of 2017.

Table 7 â&#x20AC;&#x201C; Net additional incomes generated per country per year (USD)*

Country

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

2016-2017

407,000

815,000

6,109,000

5,295,000

4,073,000

20,772,000

Timor-Leste

68,000

272,000

613,000

204,000

0**

1,157,000

Pakistan

3,294,000

12,079,000

15,373,000

13,177,000

43,923,000

Sri Lanka

448,000

1,076,000

1,524,000

PNG

214,000

428,000

642,000

Fiji

TOTAL

* Figures in italics are estimates for the remaining programme phase until 2017. Figures in bold signify results already achieved or in the process of being achieved, based on the partnerships signed in these years. All figures are rounded to the nearest thousand. ** As MDF in Timor-Leste will not add any new partnerships to the portfolio in FY 2016-2017, no additional income is shown for that year.

In Fiji, Timor-Leste and Pakistan partnerships have progressed sufficiently that actual increases in income can be measured on the ground. Overall, based on the picture emerging from Fiji and Timor-Leste portfolio of partnerships, MDF expects

MDF Results Estimates for Five Countries 2011â&#x20AC;&#x201C;2017

to overshoot on the estimates presented above. The next version of this guidance note will compare these estimates against updated additional income per beneficiary figure based on MDF actual results achieved across all countries.

CONCLUSIONS: IS MDF ON TRACK TO GENERATING TRANSFORMATIONAL CHANGE IN THE COUNTRIES IT IS ACTIVE?

Reflecting on the MDF estimates – compared to earlier estimates and with emerging projections – leads to the following conclusions:  In Fiji, partnerships have been more complex than expected, often involving multiple change steps, a series of investments and activities, and mostly taking considerably longer to implement in part caused by this complexity but also by the pace of the economy. MDF had to ‘break the mould’ of what business facilitators ‘should’ and ‘should not do’ in a small Pacific Island economy. It has succeeded in cost sharing investments in factory layout and machinery, and occasionally provided working capital and seed money. It also had to stay longer in the relationship with a partner until the oftennew enterprise could stand on its own feet, and found that business mentoring was important. This innovation in its programming is paying off. MDF will implement fewer partnerships than it originally envisioned but the results per partnership more than compensate for this. Also, the enterprises that come out at the other end of a long partnership process,process seem to sustain themselves well. This combined with the volume of change involved, the number of partnerships and the volume of investment and outreach suggests that MDF in Fiji achieve considerably more than originally estimated.  In Timor-Leste, MDF’s mission benefitted from the mould breaking done in Fiji, but also contends with Timor-Leste’s post-conflict nation building context, where public resources drive large parts of the economy. This leaves large parts of the local

economy with very little business investment and very few players and role/business models. Here MDF’s task is to ‘populate the middle segment of the economy (between the large government contracts and micro shops) with viable ‘first-oftheir-kind’ business models – sourcing from and supplying to the rural hinterland, adding value to local produce or starting to produce and make locally – what otherwise would haven imported. MDF has indeed been able to populate the economy in this manner. The results per partnership are better than expected and with more resources more would be possible. With approximately 25% of the partnerships originally envisioned MDF generates an estimated 40% of the results originally foreseen.  In both Fiji and Timor-Leste MDF met scepticism from stakeholders that market development would work (for various reasons). In Pakistan, there was the promise of being able to work in a South Asian economy similar from other economies in which market development has been proven to work well. But there are challenges, this time related to the security situation. The picture that is emerging is – perhaps not surprisingly – of an economy less hamstrung by the security situation than was predicted, but one that is more complex to navigate than some of the neighbouring economies. The gaps and disconnects seem relatively larger and more work with relatively smaller companies is needed to fill these gaps and promote genuinely new

MDF Results Estimates for Five Countries 2011–2017

business models. At the same time, the potential for significant scale remains and the general pace of the economy is good. Less than two years into implementation, MDF is still calibrating its portfolio, but nevertheless it expects to exceed the initial estimates.  For PNG and Sri Lanka it is too early to make any concluding remarks. Table 8 below summarises the estimates (cumulative totals) of all countries, across the six headline indicators. Sometime in 2017 these estimates will be revisited and modified to reflect a better understanding of all country

contexts after deeper engagement through partnerships across all identified sectors. In 2021 the results ‘books’ for this first contract phase will be closed. While the estimates for Fiji and Timor-Leste are not expected to change that much, the story is different for Pakistan, Sri Lanka and PNG. As the portfolio in Pakistan gets bigger and more mature, and as the first partnerships are rolled out in Sri Lanka and PNG, the assumptions around estimates can be validated and an updated set of estimates can be developed to improve the frame of reference within which all country results can be realistically assessed.

Table 8 – MDF results estimates for five countries, 2011 – 2017

Additional income Generated (USD)

Pakistan

Sri Lanka

PNG

TOTAL

1,157,000

43,923,000

1,524,000

642,000

68,018,000

28,407

8,670

168,000

25,092

8,040

238,209

1,430

340

7,800

2,040

315

11,925

Additional Market Transactions Recorded (USD)

3,499,000

782,000

10,800,000

2,754,000

1,400,000

19,235,000

Investment leveraged (USD)

3,499,000

1,046,000

2,185,000

918,000

690,000

8,338,000

199

2011-2017 (6 years)

2012-2017 (4.5 years)

2013-2017 (3.5 years)

2015-2017 (2 years)

Number of new jobs created (FTE)

Number of business innovations and reforms introduced Implementation window

Timor-Leste

20,772,000

Effective outreach

Fiji

MDF Results Estimates for Five Countries 2011–2017

• Fiji: Level 5, Fiji Development Bank Building, 360 Victoria Parade, Suva, Fiji Islands • Timor-Leste: 2nd Street, Palm Business & Trade Centre, Surik Mas, Dili • Pakistan: 95-E/1, Syed Shamshad Haider Road, Hali Road, Gulberg III, Lahore, Pakistan • Sri Lanka: No 18 Police Park Avenue, Colombo 5, Colombo, Sri Lanka • Papua New Guinea: Level 6, PwC Haus, Harbour City, Port Moresby, Papua New Guinea

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