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Press Release: Schroders and BlueOrchard’s Climate Impact Strategy Rapidly Attracts $ 100 Million

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Press Release: Schroders and BlueOrchard’s Climate Impact Strategy Rapidly Attracts $ 100 Million

Posted | Updated by Insights team:

Publication | Update:

Sep 2021
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Schroder ISF BlueOrchard Emerging Markets Climate Bond Fund has attracted USD 100 million in less than three months since launch.

The UCITS strategy offers daily liquidity and invests across a range of environmentally focused projects, including green bonds, and supports the United Nations’ climate-related Sustainable Development Goals.

Michael Wehrle, Head of Investment Solutions, BlueOrchard, commented:

“This milestone, and the pace at which we have achieved it, confirms our expectation that there is strong investor demand for a climate impact strategy that targets positive environmental change in emerging markets. We also believe it is a reflection of investor trust in BlueOrchard’s 20 years of experience in delivering strong results in impact and financial return.”

Carolina Minio Paluello, Global Head of Product, Solutions & Quant, Schroders, commented:

“We have identified climate change as one of the main global threats and, as investors, we possess the ability to deliver change in the world by directing capital into areas that generate positive impacts.

“This fund is enabling us to do just that and it is testament to the strengthen of our investment focus that clients also recognise this and have been keen to invest.

“The Schroder ISF BlueOrchard Emerging Markets Climate Bond Fund is enabling us to leverage our expertise and knowledge across public and private markets, to maximise our investment impact across emerging and frontier markets to help mitigate the climate challenge.”

The ever-growing investment universe of the Fund encompasses public debt securities issued for the financing and re-financing of projects with clear environmental, green or social benefits. This includes initiatives in renewable energy, energy efficiency, green buildings, and clean transportation.

The Fund also allocates part of its portfolio to sustainability and sustainability-linked bonds, with outcomes tied to the financing of both social and environmental projects. On the back of its robust investment process, BlueOrchard has built a diversified climate impact bonds portfolio with a strong bias towards emerging markets.

Among other issuers, the Fund has invested in Greenko, a leading Indian developer of renewable energy. The Fund’s investment will help to facilitate the company’s growth as a provider of climate-smart solutions in a rapidly growing market.

The Fund’s investment strategy builds on BlueOrchard’s local presence and 20-year track record in emerging and frontier market impact investing. Furthermore, the Fund benefits from BlueOrchard’s independently verified impact management and ESG investment process[1], with which BlueOrchard can implement, monitor and ultimately measure its goals and maximise the Fund’s positive impact.

Schroders completed the acquisition of a majority stake in BlueOrchard in 2019. Earlier this year, Schroders took another step towards building a leading position in sustainability and impact investments by also joining the influential Global Impact Investing Network.

BlueOrchard is an impact investment pioneer, and this year celebrates its 20th anniversary.  Since its inception in 2001, BlueOrchard has evolved into a leading global impact investment manager, having invested more than USD 8 billion across more than 90 countries to date. As of March 2021, more than 216 million poor and vulnerable people, in emerging and frontier markets, have received access to financial and related services with the support of BlueOrchard.

[1] BlueOrchard is signatory to the Operating Principles for Impact Management since April 2019. As part of this commitment, its impact management framework B.Impact, has been independently verified one year after by BlueMark, a Tideline company, and a leading provider of independent impact verification services for investors and companies.

Photo courtesy of Franz Jachim.

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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